init: Any2Ego code, README and checkpoint indexes

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer.json filter=lfs diff=lfs merge=lfs -text

CHECKSUMS.sha256

@@ -0,0 +1,77 @@
+ab3d52dfcbe208855e491e87289fe5e9eed25047d5c4f2c8a2a49948b7b5e5c7  README.md
+4e0e37529fbf86ebef6bf7cadec4dda1b762f31ed6dba7815a79732bc6b7e836  checkpoints/caption_grpo/adapter_config.json
+290aacd2808639e3c3e10c81c69acfdd843100b8888ad183a2e03ba6e43f5d11  checkpoints/caption_grpo/adapter_model.safetensors
+62671bc8d430001734a90c33c0059e563388eba42706a5c8603704018035ae8b  checkpoints/caption_grpo/additional_config.json
+f7b83d712eac12caeb772d926165fce76b2ac02a413536f354d875d40ed345aa  checkpoints/generator_global/ckpt.safetensors
+16760be1abceff62f816e2837ba6517ea84d504263f37cc756d5cc3eb627c68d  checkpoints/generator_hoi/ckpt.safetensors
+940a2bc83f63056d4672562947e9ae503b1489932f41b1a917e5d0a8285f9fe0  checkpoints/generator_spatial/ckpt.safetensors
+3dccf97f938c22f6143020164431a956e0b6335439a691a9b38af99a7d62ba7d  checkpoints/mask_predictor/ckpt.pt
+79732eef0f1efbb90b8d7090fb17b4946cc7b84e1915b57995bf3536f2559e55  checkpoints/reward_preview/ckpt.safetensors
+0a9dd840ab4d8c0c91927f8b53a24981bd5f475e4fb9d4556e825593846e7d65  checkpoints/sft_only/adapter_config.json
+072df399b4320b17313a64fb7c024d1f981464e9852c979f4644391e77853f2e  checkpoints/sft_only/adapter_model.safetensors
+62671bc8d430001734a90c33c0059e563388eba42706a5c8603704018035ae8b  checkpoints/sft_only/additional_config.json
+c3882d05e91dd7cc4ad55d4f5d56d001c1cf028a16aa33e491a833bfb3d6583a  code_support/diffusion/infer_caption.py
+db5e8bfe8d5ff45e0dc29dfcbdb1bab4e70febd9d66dedc46a1f6404f73224fb  code_support/diffusion/infer_vace_hoi.py
+48195fb1515b26d0bc6440db02d3181bd1ab536143bc44b5c251c7247b2cdc4a  code_support/generator_defaults.py
+2b99845ed2bdc5cdc1b78acadaca99b37af672a83e061b3f7aeb0f45dcf47d63  code_support/loader_patch.json
+d7449d7c527adbe7645d1ffe1942e22cc411ad7afe59a40f652ebf5da3f1daf1  code_support/model_resources.py
+b72278058c6afe6f3ec66cf960cc66c92187fd4ab118a6deb8630da87a73610a  code_support/project_paths.py
+2d1000a1f8a4ef8d1ae30a425d9e3fc23c6255bc5052bbb777508bc2489ade8f  models/CLIP-ViT-H-14-laion2B-s32B-b79K/README.md
+14db420f00ddf78a07194dc4cdc57977d979e0f2c34994137679046defdf6577  models/CLIP-ViT-H-14-laion2B-s32B-b79K/UPSTREAM_README.md
+50150597fccadc90f3198d1c2caf2c41d88a40908c38fb428ea56c249b501d85  models/CLIP-ViT-H-14-laion2B-s32B-b79K/config.json
+f1cd414c2d113a28b296afc0fd66ae854c0e0c34d5de373a2f5b7f62e0c02344  models/CLIP-ViT-H-14-laion2B-s32B-b79K/merges.txt
+036e6e2bd49697511f4f8b8cb5ee465f93025f7a69a145eadeb9a881ace9b18d  models/CLIP-ViT-H-14-laion2B-s32B-b79K/model.safetensors
+910e70b3956ac9879ebc90b22fb3bc8a75b6a0677814500101a4c072bd7857bd  models/CLIP-ViT-H-14-laion2B-s32B-b79K/preprocessor_config.json
+f8c0d6c39aee3f8431078ef6646567b0aba7f2246e9c54b8b99d55c22b707cbf  models/CLIP-ViT-H-14-laion2B-s32B-b79K/special_tokens_map.json
+b556ac8c99757ffb677208af34bc8c6721572114111a6e0aaf5fa69ff0b8d842  models/CLIP-ViT-H-14-laion2B-s32B-b79K/tokenizer.json
+e19f34ef773563fb695f96cfcae1e4c7b112ab6ad532f6962061df5242d924f0  models/CLIP-ViT-H-14-laion2B-s32B-b79K/tokenizer_config.json
+5047b556ce86ccaf6aa22b3ffccfc52d391ea4accdab9c2f2407da5b742d4363  models/CLIP-ViT-H-14-laion2B-s32B-b79K/vocab.json
+6d5d06e0c3f069097002445d30dce9ee107db3afaf15563f09e6df49b8dcb4d7  models/Qwen3-VL-8B-Instruct/README.md
+5c72a170d2a4a1a3bc5adad2e689ae28138a9700e5b8c96c0266331e86c0acce  models/Qwen3-VL-8B-Instruct/chat_template.json
+5cd452860dc1e9c29dd71cc3cef7f39b338b7a40793f7a260655c2d3568f3661  models/Qwen3-VL-8B-Instruct/config.json
+8469742d1fce0de951c8909b26a2c0c0d8490837ce476efb114da9e0cefc4d44  models/Qwen3-VL-8B-Instruct/generation_config.json
+599bab54075088774b1733fde865d5bd747cbcc7a547c5bc12610e874e26f5e3  models/Qwen3-VL-8B-Instruct/merges.txt
+d5d0aef0eb170fc7453a296c43c0849a56f510555d3588e4fd662bb35490aefa  models/Qwen3-VL-8B-Instruct/model-00001-of-00004.safetensors
+8be88fb5501e4d5719a6d4cc212e6a13480330e74f3e8c77daa1a68f199106b5  models/Qwen3-VL-8B-Instruct/model-00002-of-00004.safetensors
+83de00eafe6e0d57ccd009dbcf71c9974d74df2f016c27afb7e95aafd16b2192  models/Qwen3-VL-8B-Instruct/model-00003-of-00004.safetensors
+0a88b98e9f96270973f567e6a2c103ede6ccdf915ca3075e21c755604d0377a5  models/Qwen3-VL-8B-Instruct/model-00004-of-00004.safetensors
+520b2e05079402e9468a8701d03d1154d14b2599593afb6effa7fb60c1bff070  models/Qwen3-VL-8B-Instruct/model.safetensors.index.json
+27225450ac9c6529872ee1924fcb0962ff5634834f817040f444118116f4e516  models/Qwen3-VL-8B-Instruct/preprocessor_config.json
+a5d85b6dcc535e6b93115a9ef287e6132fdbf30270da6218194ba742261173c7  models/Qwen3-VL-8B-Instruct/tokenizer.json
+c2da771801886ad9ae98181793ffd3dfb7f1af30f6f7c6a4e15d7dbba52e2399  models/Qwen3-VL-8B-Instruct/tokenizer_config.json
+7768af27c1fafa9cc9011c1dc20067e03f8915e03b63504550e11d5066986d13  models/Qwen3-VL-8B-Instruct/video_preprocessor_config.json
+149e96be859017f8ae661c1b2451dc8fa7ff7a26abb8b95b050187c78a1a4b69  models/Qwen3-VL-8B-Instruct/vocab.json
+c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4  models/Wan2.1-VACE-1.3B/LICENSE.txt
+6bd8ab0b7ed64223fe254bfdee66bef4069801fe975ceccff2bdd0708ba321ac  models/Wan2.1-VACE-1.3B/README.md
+38071ab59bd94681c686fa51d75a1968f64e470262043be31f7a094e442fd981  models/Wan2.1-VACE-1.3B/Wan2.1_VAE.pth
+e19df24acf3f440e0aea37d299f22b96f88d164f3349ae696daecd960a35ab1e  models/Wan2.1-VACE-1.3B/config.json
+7b8a9f5040adb67b5805abdfd42c1f8d0f3d0e711f10726580eb3789cd0ad61d  models/Wan2.1-VACE-1.3B/google/umt5-xxl/special_tokens_map.json
+e3909a67b780650b35cf529ac782ad2b6b26e6d1f849d3fbb6a872905f452458  models/Wan2.1-VACE-1.3B/google/umt5-xxl/spiece.model
+6e197b4d3dbd71da14b4eb255f4fa91c9c1f2068b20a2de2472967ca3d22602b  models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer.json
+ed9a3a8b0faa71a70a32847e0435fe036e6e112d4df4edb7bb48a921e344dc05  models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer_config.json
+4e31340625635eea1f0d0935e5ff1a3e47689cb38088ad40b1dcd06add1bc0c5  models/Wan2.1-VACE-1.3B/model_components.json
+9e230513fc75b9ca1f432d1f6ef92a7416ff2e0e02f20ef50d6bc789b6d40747  models/Wan2.1-VACE-1.3B/text_encoder/README.md
+19455304c63fe471f7241a6785ef804b8012edd8ce9f30c74e8825f03413c96b  models/Wan2.1-VACE-1.3B/text_encoder/model-00001-of-00003.safetensors
+5cbed706d3edd448e4d32188892cd87ed8a1223207d2482d09a40ca4cfbed6ab  models/Wan2.1-VACE-1.3B/text_encoder/model-00002-of-00003.safetensors
+e56bfcc518f43f1fd83727e673cc121a171594082fc9e14164179363fbccc182  models/Wan2.1-VACE-1.3B/text_encoder/model-00003-of-00003.safetensors
+8322567493a4f08dce5d97f8621a2896a5ed1b72e0865371e3339599e077ebb2  models/Wan2.1-VACE-1.3B/text_encoder/model.safetensors.index.json
+b2cc0414f6693d95f0486fe9cf1e60b8f9757b6a578855421c1a3bc50e14feae  models/Wan2.1-VACE-1.3B/text_encoder/reshard_manifest.json
+90bd23f138e69e6099f7634993b32ed066fe92a604b396a9387bf6d167017839  models/Wan2.1-VACE-1.3B/transformer/README.md
+3b611c672b94037e07d90c4374e5b17eea45a5abe4a090f2875b67dd120a83d2  models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model-00001-of-00002.safetensors
+4dff7356c1b66cb9519ab669a78f46e7a03eb5aca60c3588348f5d4285495e8f  models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model-00002-of-00002.safetensors
+b6e35916452ede069646051df78656ff577474db05d4bfc435b81f18fdeebb7d  models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model.safetensors.index.json
+c73909909d5241a3816896220a2b72705c0078fbf034848b154183aada36e6c8  models/Wan2.1-VACE-1.3B/transformer/reshard_manifest.json
+7c6f40d2ae7126dd35e92e29d38bb47c459318711fdb26ba72201f5cd82fcaf7  native_reader_validation.json
+ff13d7f409c6392a00f3dfcb42c32fccb11c77b4ad2f721e276fe96513017bbf  research/caption_dpo/epoch-2.safetensors
+522d9ff9e721ab7ee9a7272a6dfbdf0aaedb1c6c4e8f5fa1d9b27ac73ba0fad0  research/joint_branch/epoch-3.safetensors
+4cd0d08b16782c7ca3566db23d378b206880203f013b3c017791712aa66d0704  research/mask_predictor_paperalign/epoch-4.pt
+a112106d5a2bd851c3a635ac752268aa8154a1eab5101d4ee762f97f64fa3b1a  research/native_narr_dit/epoch-4.safetensors
+f6abd392ec7b18e182c1e4c0e840794aa29c629036b290c013fe6ee4c0df1de4  research/vlm_comparison/epoch-0.safetensors
+02c24bf6017a2450411d6a6056b6004107b453239b3c61c5f729a6f31e84f9be  tools/attach_model_bundle.py
+45dd80eda5ebd3a4545678a4567eb702fac1631a6a830fec07cf708c35d41a46  tools/prepare_egoexo_model_bundle.py
+cab58ac00a4acda90cda76cf00cf9e3f7bb8e883b596653db6ee4efec81d7034  tools/reshard_weights.py
+caf3c1f8a36bd4d4fa3e4327438dc22a962cb7b43369254e235f74c926cd4832  tools/tests/test_attach_model_bundle.py
+16162f1dc790a511a797a1f4b4ec9d402ea08c8579db005bee128ed5368533ce  tools/tests/test_model_resources.py
+e16945ecb5331cc97730bc6f3a704dfc2f50e69501c61ada177d06bdce347ea9  tools/tests/test_reshard_weights.py
+c602d4305f59c388105765835b3b7d9cacf2181e8494014fea7f0dc57e728cb8  tools/verify_model_bundle.py
+e399d0e864fbf8d9093d52bcf5f7770904e0ac4e4b1b1857dbc502857b15a0a1  bundle_manifest.json

README.md

@@ -1,3 +1,102 @@
 ---
-license: mit
+tags:
+- exo-to-ego
+- video-generation
+- safetensors
+- lora
+- research
 ---
+# Ego-Exo / Any2Ego — 5GB 分片权重包
+
+**发布的是已有研究检查点与基础模型的无损分片，不是新训练结果。** 所有文件不超过
+5,000,000,000 字节（包含 safetensors 头）。不是 split/tar 片段；
+模型张量保留完整，一个张量不会被切成两半。原始模型/检查点没有修改。
+
+## 目录与分片
+
+- `models/Wan2.1-VACE-1.3B/transformer/`：原生 DiT+VACE 底座，2 片；
+  `diffusion_pytorch_model.safetensors.index.json`。
+- `models/Wan2.1-VACE-1.3B/text_encoder/`：原生 umT5-XXL BF16，3 片；
+  `model.safetensors.index.json`。原 .pth 的完整存储逐字节转存 safetensors，
+  不改变 key、shape、dtype 或值；只用 weights_only/FakeTensor 读取元信息。
+- Wan VAE 和 `google/umt5-xxl/` tokenizer 保留原格式。
+- `models/Qwen3-VL-8B-Instruct/`：官方基座原有 4 片已小于 5GB，完整保留。
+- `models/CLIP-ViT-H-14-laion2B-s32B-b79K/`：Transformers 格式原单文件保留；
+  未重复打包 OpenCLIP/bin 副本。
+- `checkpoints/`：7 个主链路训练产物；`research/`：5 个辅助实验快照。
+  它们本来就小于 5GB，保留原 safetensors/.pt 与必要的 adapter 配置。
+- `code_support/`、`tools/`：分片加载兼容补丁、校验/安装/重新分片工具与 CPU 小测试。
+
+基础模型仍是上游模型，不是合并后的 Any2Ego 训练权重；没有合并 LoRA。
+上游模型各自遵守原许可证，不能把整个 bundle 统一声明为新的自有模型。
+训练数据、caption、视频、optimizer/RNG/log/缓存不包含在这个**权重包**里。
+
+## 训练产物选择
+
+| Component | MiB | 来源/选择 |
+|---|---:|---|
+| generator_hoi | 166.9 | paper-index HOI LoRA, epoch4 |
+| generator_global | 630.4 | paper-index Global caption branch, epoch4 |
+| generator_spatial | 630.5 | paper-index Spatial caption branch, epoch2; historical teacher caption training |
+| reward_preview | 630.4 | teacher-caption Global reward preview, epoch4 |
+| mask_predictor | 21.2 | historical evaluated PhiSeg, epoch9; exo_full_context/BN settings must match |
+| sft_only | 83.3 | Qwen3-VL-8B LoRA, step4070 |
+| caption_grpo | 83.3 | Qwen3-VL-8B GRPO LoRA, step3800 |
+| mask_predictor_paperalign_candidate | 21.2 | last existing paper-align checkpoint, not validated best/final |
+| vlm_comparison | 720.4 | paper-index continuous VLM comparison, epoch0 |
+| joint_branch | 1350.8 | last normal joint checkpoint; gate-edited ablations excluded |
+| caption_dpo | 630.4 | last available DPO checkpoint, not asserted best |
+| native_narr_dit | 333.8 | native narration DiT LoRA, epoch4 |
+
+Historical Spatial epoch2 使用 teacher captions 训练，不冒称新的 GRPO-caption
+重训结果；PhiSeg epoch9 对应 exo_full_context/BN 实验支路，推理需匹配
+`--exo_full_context --bn_batch_stats` 与数据设置。paperalign epoch4 只是候选，
+未声明最佳/收敛。辅助 joint/VLM/DPO/native-narr 权重不可替代主分支。
+SFT/GRPO 为 Qwen3-VL-8B 的 rank16/alpha32 LoRA，非机器人项目的 27B 权重。
+Adapter 权重原样保留，配置只将基座路径规范为官方 Qwen ID。
+
+## 接到现有代码（不会自动训练或推理）
+
+GitHub 源码：`https://github.com/coisini-gif/exo-ego-video-converter`（私密仓库需访问权限）。
+下载权重包后，在源码 checkout 的 `code/core` 下使用模型。
+
+```bash
+BUNDLE=/your/downloaded/ego_exo_5gb_20261102
+CORE=/your/exo-ego-video-converter/code/core
+# 先看计划；无写入、无模型加载
+python "$BUNDLE/tools/attach_model_bundle.py" --bundle "$BUNDLE" --code-root "$CORE"
+# 仅对不存在的资源建链接，旧版 loader 按已知 SHA256 安全补丁；有自定义改动会拒绝覆盖
+python "$BUNDLE/tools/attach_model_bundle.py" --bundle "$BUNDLE" --code-root "$CORE" --apply
+# 文件完整性校验（需要读完整包，但不使用 GPU）
+python "$BUNDLE/tools/verify_model_bundle.py" --bundle "$BUNDLE"
+```
+
+Wan 的这两个索引**不能直接传入旧版二进制 loader**。兼容补丁分别把
+DiT、T5 的 shard 列表传给一个 `ModelConfig(path=[...])`，再加入 VAE；
+已覆盖 HOI/Global/Spatial 推理、generator training defaults 和 reward preview
+共用的 build_pipe。原单文件路径仍然兼容，`WAN_MODEL_ROOT` 可覆盖 Wan 位置。
+这不是标准 diffusers 架构转换；不要直接对 Wan 分片子目录调用
+`transformers.AutoModel.from_pretrained`，也不需要先合并回 >5GB 文件。
+
+若用 research 旧入口，设置 `MODEL_ROOT=$BUNDLE/models`，并显式指定对应
+`$BUNDLE/research/...` 检查点；这些旧入口仍需用 `wan_model_paths` 解析 Wan
+组件，或采用 core 主入口。未声称所有历史脚本均已自动改为分片加载。
+运行推理/训练还需要论文对应数据、mask、caption、第三方框架和正确版本。
+**权重完整性校验并不等于完整 GPU 复现或论��指标复现。**
+
+## 校验与 HF
+
+`bundle_manifest.json` / `CHECKSUMS.sha256` 提供文件哈希；两个大组件各自的
+`reshard_manifest.json` 还包含每个原张量的 SHA256，输出独立回读逐张量验证。
+`native_reader_validation.json` 使用原生 safetensors CPU reader 验证所有
+名称、形状和 dtype，未实例化模型/分配 GPU。
+
+整个目录可作为 **private HF model repo** 的上传目录（含模型/权重 README）。
+如只发布自训产物，可仅上传 `checkpoints/` 和 `research/`，依赖官方基座。
+本地分片流程**没有运行网络上传**；本包分发目标为 `diffusion-gif/any2ego` 私有模型仓。GitHub token
+不能用于 HF。不保存或打包密钥。可在 HF 单独建 repo 后使用 `hf upload`
+或 huggingface_hub 上传目录；Wan 模型资源布局需保留不变。
+
+## 分发与导出记录
+
+分发目标：`diffusion-gif/any2ego`，`model`，Private。基座与自训权重未合并，原张量内容未改变。`bundle_manifest.json` 中的 `upload_run=false` 等运行字段描述原始**本地导出阶段**，不是此 HF 仓库的传输状态。分发版只调整 README 的分发说明并相应更新文件校验清单；数据和密钥不在包内。

bundle_manifest.json

@@ -0,0 +1,580 @@
+{
+  "schema_version": 1,
+  "status": "complete",
+  "created_at_UTC": "2026-11-02T14:44:04.758486+00:00",
+  "sources": {
+    "project_root": "/pfs/zhangyuxuan/ego-exo/egoexo_gen",
+    "wan_base": "/pfs/shared_models/Wan2.1-VACE-1.3B",
+    "vlm_base": "/pfs/shared_models/Qwen3-VL-8B-Instruct",
+    "clip_base": "/pfs/shared_models/CLIP-ViT-H-14-laion2B-s32B-b79K",
+    "max_file_bytes": 5000000000
+  },
+  "max_file_bytes": 5000000000,
+  "trained_components": [
+    {
+      "component": "generator_hoi",
+      "source": "outputs/train_vace_hoi_lora_r128_sq_sq480/epoch-4.safetensors",
+      "path": "checkpoints/generator_hoi/ckpt.safetensors",
+      "selection": "paper-index HOI LoRA, epoch4",
+      "sha256": "16760be1abceff62f816e2837ba6517ea84d504263f37cc756d5cc3eb627c68d",
+      "bytes": 175017544,
+      "format_preserved": true,
+      "tensor_count": 300,
+      "has_spatial_route": false
+    },
+    {
+      "component": "generator_global",
+      "source": "outputs/train_caption_hoi_v2clean_sq_sq480/epoch-4.safetensors",
+      "path": "checkpoints/generator_global/ckpt.safetensors",
+      "selection": "paper-index Global caption branch, epoch4",
+      "sha256": "f7b83d712eac12caeb772d926165fce76b2ac02a413536f354d875d40ed345aa",
+      "bytes": 660999544,
+      "format_preserved": true,
+      "tensor_count": 240,
+      "has_spatial_route": false
+    },
+    {
+      "component": "generator_spatial",
+      "source": "outputs/train_caption_hoi_v2clean_sq_teacher_sroute_capdrop15/epoch-2.safetensors",
+      "path": "checkpoints/generator_spatial/ckpt.safetensors",
+      "selection": "paper-index Spatial caption branch, epoch2; historical teacher caption training",
+      "sha256": "940a2bc83f63056d4672562947e9ae503b1489932f41b1a917e5d0a8285f9fe0",
+      "bytes": 661099140,
+      "format_preserved": true,
+      "tensor_count": 300,
+      "has_spatial_route": true
+    },
+    {
+      "component": "reward_preview",
+      "source": "outputs/train_caption_hoi_v2clean_sq_teacher_oracle_capdrop15/epoch-4.safetensors",
+      "path": "checkpoints/reward_preview/ckpt.safetensors",
+      "selection": "teacher-caption Global reward preview, epoch4",
+      "sha256": "79732eef0f1efbb90b8d7090fb17b4946cc7b84e1915b57995bf3536f2559e55",
+      "bytes": 660999544,
+      "format_preserved": true,
+      "tensor_count": 240,
+      "has_spatial_route": false
+    },
+    {
+      "component": "mask_predictor",
+      "source": "outputs/train_phiseg_bugfix_exofull/epoch-9.pt",
+      "path": "checkpoints/mask_predictor/ckpt.pt",
+      "selection": "historical evaluated PhiSeg, epoch9; exo_full_context/BN settings must match",
+      "sha256": "3dccf97f938c22f6143020164431a956e0b6335439a691a9b38af99a7d62ba7d",
+      "bytes": 22230487,
+      "format_preserved": true
+    },
+    {
+      "component": "sft_only",
+      "source": "outputs/train_student_qwen_b200fix/v0-20260911-034450/checkpoint-4070/adapter_model.safetensors",
+      "path": "checkpoints/sft_only/adapter_model.safetensors",
+      "selection": "Qwen3-VL-8B LoRA, step4070",
+      "sha256": "072df399b4320b17313a64fb7c024d1f981464e9852c979f4644391e77853f2e",
+      "bytes": 87369152,
+      "format_preserved": true,
+      "tensor_count": 504,
+      "has_spatial_route": false,
+      "config_normalization": "only base_model_name_or_path normalized to official Qwen ID"
+    },
+    {
+      "component": "caption_grpo",
+      "source": "outputs/train_captioner_grpo/v2-20260917-122629/checkpoint-3800/adapter_model.safetensors",
+      "path": "checkpoints/caption_grpo/adapter_model.safetensors",
+      "selection": "Qwen3-VL-8B GRPO LoRA, step3800",
+      "sha256": "290aacd2808639e3c3e10c81c69acfdd843100b8888ad183a2e03ba6e43f5d11",
+      "bytes": 87369152,
+      "format_preserved": true,
+      "tensor_count": 504,
+      "has_spatial_route": false,
+      "config_normalization": "only base_model_name_or_path normalized to official Qwen ID"
+    },
+    {
+      "component": "mask_predictor_paperalign_candidate",
+      "source": "outputs/train_phiseg_paperalign/epoch-4.pt",
+      "path": "research/mask_predictor_paperalign/epoch-4.pt",
+      "selection": "last existing paper-align checkpoint, not validated best/final",
+      "sha256": "4cd0d08b16782c7ca3566db23d378b206880203f013b3c017791712aa66d0704",
+      "bytes": 22230487,
+      "format_preserved": true
+    },
+    {
+      "component": "vlm_comparison",
+      "source": "outputs/train_vlm_hoi_sq480/epoch-0.safetensors",
+      "path": "research/vlm_comparison/epoch-0.safetensors",
+      "selection": "paper-index continuous VLM comparison, epoch0",
+      "sha256": "f6abd392ec7b18e182c1e4c0e840794aa29c629036b290c013fe6ee4c0df1de4",
+      "bytes": 755371392,
+      "format_preserved": true,
+      "tensor_count": 240,
+      "has_spatial_route": false
+    },
+    {
+      "component": "joint_branch",
+      "source": "outputs/train_joint_hoi/epoch-3.safetensors",
+      "path": "research/joint_branch/epoch-3.safetensors",
+      "selection": "last normal joint checkpoint; gate-edited ablations excluded",
+      "sha256": "522d9ff9e721ab7ee9a7272a6dfbdf0aaedb1c6c4e8f5fa1d9b27ac73ba0fad0",
+      "bytes": 1416371272,
+      "format_preserved": true,
+      "tensor_count": 480,
+      "has_spatial_route": false
+    },
+    {
+      "component": "caption_dpo",
+      "source": "outputs/train_caption_dpo_v2clean_sq_sq480/epoch-2.safetensors",
+      "path": "research/caption_dpo/epoch-2.safetensors",
+      "selection": "last available DPO checkpoint, not asserted best",
+      "sha256": "ff13d7f409c6392a00f3dfcb42c32fccb11c77b4ad2f721e276fe96513017bbf",
+      "bytes": 660999900,
+      "format_preserved": true,
+      "tensor_count": 240,
+      "has_spatial_route": false
+    },
+    {
+      "component": "native_narr_dit",
+      "source": "outputs/train_narr_caption_dit_r128/epoch-4.safetensors",
+      "path": "research/native_narr_dit/epoch-4.safetensors",
+      "selection": "native narration DiT LoRA, epoch4",
+      "sha256": "a112106d5a2bd851c3a635ac752268aa8154a1eab5101d4ee762f97f64fa3b1a",
+      "bytes": 350032624,
+      "format_preserved": true,
+      "tensor_count": 600,
+      "has_spatial_route": false
+    }
+  ],
+  "base_components": [
+    {
+      "component": "wan_transformer",
+      "path": "models/Wan2.1-VACE-1.3B/transformer",
+      "shard_count": 2,
+      "tensor_count": 1264
+    },
+    {
+      "component": "wan_text_encoder",
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder",
+      "shard_count": 3,
+      "tensor_count": 242
+    },
+    {
+      "component": "captioner_base",
+      "base_model": "Qwen/Qwen3-VL-8B-Instruct",
+      "path": "models/Qwen3-VL-8B-Instruct",
+      "shard_count": 4,
+      "tensor_count": 750,
+      "unchanged_original_shards": true,
+      "raw_tensor_bytes": 17534247392
+    },
+    {
+      "component": "reward_clip_base",
+      "base_model": "laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K",
+      "shard_count": 1,
+      "tensor_count": 912,
+      "format_preserved": true
+    }
+  ],
+  "files": [
+    {
+      "path": "README.md",
+      "bytes": 6249,
+      "sha256": "ab3d52dfcbe208855e491e87289fe5e9eed25047d5c4f2c8a2a49948b7b5e5c7"
+    },
+    {
+      "path": "checkpoints/caption_grpo/adapter_config.json",
+      "bytes": 1091,
+      "sha256": "4e0e37529fbf86ebef6bf7cadec4dda1b762f31ed6dba7815a79732bc6b7e836"
+    },
+    {
+      "path": "checkpoints/caption_grpo/adapter_model.safetensors",
+      "bytes": 87369152,
+      "sha256": "290aacd2808639e3c3e10c81c69acfdd843100b8888ad183a2e03ba6e43f5d11"
+    },
+    {
+      "path": "checkpoints/caption_grpo/additional_config.json",
+      "bytes": 76,
+      "sha256": "62671bc8d430001734a90c33c0059e563388eba42706a5c8603704018035ae8b"
+    },
+    {
+      "path": "checkpoints/generator_global/ckpt.safetensors",
+      "bytes": 660999544,
+      "sha256": "f7b83d712eac12caeb772d926165fce76b2ac02a413536f354d875d40ed345aa"
+    },
+    {
+      "path": "checkpoints/generator_hoi/ckpt.safetensors",
+      "bytes": 175017544,
+      "sha256": "16760be1abceff62f816e2837ba6517ea84d504263f37cc756d5cc3eb627c68d"
+    },
+    {
+      "path": "checkpoints/generator_spatial/ckpt.safetensors",
+      "bytes": 661099140,
+      "sha256": "940a2bc83f63056d4672562947e9ae503b1489932f41b1a917e5d0a8285f9fe0"
+    },
+    {
+      "path": "checkpoints/mask_predictor/ckpt.pt",
+      "bytes": 22230487,
+      "sha256": "3dccf97f938c22f6143020164431a956e0b6335439a691a9b38af99a7d62ba7d"
+    },
+    {
+      "path": "checkpoints/reward_preview/ckpt.safetensors",
+      "bytes": 660999544,
+      "sha256": "79732eef0f1efbb90b8d7090fb17b4946cc7b84e1915b57995bf3536f2559e55"
+    },
+    {
+      "path": "checkpoints/sft_only/adapter_config.json",
+      "bytes": 1091,
+      "sha256": "0a9dd840ab4d8c0c91927f8b53a24981bd5f475e4fb9d4556e825593846e7d65"
+    },
+    {
+      "path": "checkpoints/sft_only/adapter_model.safetensors",
+      "bytes": 87369152,
+      "sha256": "072df399b4320b17313a64fb7c024d1f981464e9852c979f4644391e77853f2e"
+    },
+    {
+      "path": "checkpoints/sft_only/additional_config.json",
+      "bytes": 76,
+      "sha256": "62671bc8d430001734a90c33c0059e563388eba42706a5c8603704018035ae8b"
+    },
+    {
+      "path": "code_support/diffusion/infer_caption.py",
+      "bytes": 9044,
+      "sha256": "c3882d05e91dd7cc4ad55d4f5d56d001c1cf028a16aa33e491a833bfb3d6583a"
+    },
+    {
+      "path": "code_support/diffusion/infer_vace_hoi.py",
+      "bytes": 5005,
+      "sha256": "db5e8bfe8d5ff45e0dc29dfcbdb1bab4e70febd9d66dedc46a1f6404f73224fb"
+    },
+    {
+      "path": "code_support/generator_defaults.py",
+      "bytes": 1494,
+      "sha256": "48195fb1515b26d0bc6440db02d3181bd1ab536143bc44b5c251c7247b2cdc4a"
+    },
+    {
+      "path": "code_support/loader_patch.json",
+      "bytes": 985,
+      "sha256": "2b99845ed2bdc5cdc1b78acadaca99b37af672a83e061b3f7aeb0f45dcf47d63"
+    },
+    {
+      "path": "code_support/model_resources.py",
+      "bytes": 2861,
+      "sha256": "d7449d7c527adbe7645d1ffe1942e22cc411ad7afe59a40f652ebf5da3f1daf1"
+    },
+    {
+      "path": "code_support/project_paths.py",
+      "bytes": 1030,
+      "sha256": "b72278058c6afe6f3ec66cf960cc66c92187fd4ab118a6deb8630da87a73610a"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/README.md",
+      "bytes": 525,
+      "sha256": "2d1000a1f8a4ef8d1ae30a425d9e3fc23c6255bc5052bbb777508bc2489ade8f"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/UPSTREAM_README.md",
+      "bytes": 8209,
+      "sha256": "14db420f00ddf78a07194dc4cdc57977d979e0f2c34994137679046defdf6577"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/config.json",
+      "bytes": 4725,
+      "sha256": "50150597fccadc90f3198d1c2caf2c41d88a40908c38fb428ea56c249b501d85"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/merges.txt",
+      "bytes": 524618,
+      "sha256": "f1cd414c2d113a28b296afc0fd66ae854c0e0c34d5de373a2f5b7f62e0c02344"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/model.safetensors",
+      "bytes": 3944552236,
+      "sha256": "036e6e2bd49697511f4f8b8cb5ee465f93025f7a69a145eadeb9a881ace9b18d"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/preprocessor_config.json",
+      "bytes": 316,
+      "sha256": "910e70b3956ac9879ebc90b22fb3bc8a75b6a0677814500101a4c072bd7857bd"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/special_tokens_map.json",
+      "bytes": 389,
+      "sha256": "f8c0d6c39aee3f8431078ef6646567b0aba7f2246e9c54b8b99d55c22b707cbf"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/tokenizer.json",
+      "bytes": 2224041,
+      "sha256": "b556ac8c99757ffb677208af34bc8c6721572114111a6e0aaf5fa69ff0b8d842"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/tokenizer_config.json",
+      "bytes": 904,
+      "sha256": "e19f34ef773563fb695f96cfcae1e4c7b112ab6ad532f6962061df5242d924f0"
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/vocab.json",
+      "bytes": 862328,
+      "sha256": "5047b556ce86ccaf6aa22b3ffccfc52d391ea4accdab9c2f2407da5b742d4363"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/README.md",
+      "bytes": 7133,
+      "sha256": "6d5d06e0c3f069097002445d30dce9ee107db3afaf15563f09e6df49b8dcb4d7"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/chat_template.json",
+      "bytes": 5499,
+      "sha256": "5c72a170d2a4a1a3bc5adad2e689ae28138a9700e5b8c96c0266331e86c0acce"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/config.json",
+      "bytes": 1474,
+      "sha256": "5cd452860dc1e9c29dd71cc3cef7f39b338b7a40793f7a260655c2d3568f3661"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/generation_config.json",
+      "bytes": 269,
+      "sha256": "8469742d1fce0de951c8909b26a2c0c0d8490837ce476efb114da9e0cefc4d44"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/merges.txt",
+      "bytes": 1671839,
+      "sha256": "599bab54075088774b1733fde865d5bd747cbcc7a547c5bc12610e874e26f5e3"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00001-of-00004.safetensors",
+      "bytes": 4902275944,
+      "sha256": "d5d0aef0eb170fc7453a296c43c0849a56f510555d3588e4fd662bb35490aefa"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00002-of-00004.safetensors",
+      "bytes": 4915962496,
+      "sha256": "8be88fb5501e4d5719a6d4cc212e6a13480330e74f3e8c77daa1a68f199106b5"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00003-of-00004.safetensors",
+      "bytes": 4999831048,
+      "sha256": "83de00eafe6e0d57ccd009dbcf71c9974d74df2f016c27afb7e95aafd16b2192"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00004-of-00004.safetensors",
+      "bytes": 2716270024,
+      "sha256": "0a88b98e9f96270973f567e6a2c103ede6ccdf915ca3075e21c755604d0377a5"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model.safetensors.index.json",
+      "bytes": 67759,
+      "sha256": "520b2e05079402e9468a8701d03d1154d14b2599593afb6effa7fb60c1bff070"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/preprocessor_config.json",
+      "bytes": 390,
+      "sha256": "27225450ac9c6529872ee1924fcb0962ff5634834f817040f444118116f4e516"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/tokenizer.json",
+      "bytes": 7032403,
+      "sha256": "a5d85b6dcc535e6b93115a9ef287e6132fdbf30270da6218194ba742261173c7"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/tokenizer_config.json",
+      "bytes": 10868,
+      "sha256": "c2da771801886ad9ae98181793ffd3dfb7f1af30f6f7c6a4e15d7dbba52e2399"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/video_preprocessor_config.json",
+      "bytes": 385,
+      "sha256": "7768af27c1fafa9cc9011c1dc20067e03f8915e03b63504550e11d5066986d13"
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/vocab.json",
+      "bytes": 3686692,
+      "sha256": "149e96be859017f8ae661c1b2451dc8fa7ff7a26abb8b95b050187c78a1a4b69"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/LICENSE.txt",
+      "bytes": 11357,
+      "sha256": "c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/README.md",
+      "bytes": 483,
+      "sha256": "6bd8ab0b7ed64223fe254bfdee66bef4069801fe975ceccff2bdd0708ba321ac"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/Wan2.1_VAE.pth",
+      "bytes": 507609880,
+      "sha256": "38071ab59bd94681c686fa51d75a1968f64e470262043be31f7a094e442fd981"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/config.json",
+      "bytes": 349,
+      "sha256": "e19df24acf3f440e0aea37d299f22b96f88d164f3349ae696daecd960a35ab1e"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/google/umt5-xxl/special_tokens_map.json",
+      "bytes": 6623,
+      "sha256": "7b8a9f5040adb67b5805abdfd42c1f8d0f3d0e711f10726580eb3789cd0ad61d"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/google/umt5-xxl/spiece.model",
+      "bytes": 4548313,
+      "sha256": "e3909a67b780650b35cf529ac782ad2b6b26e6d1f849d3fbb6a872905f452458"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer.json",
+      "bytes": 16837417,
+      "sha256": "6e197b4d3dbd71da14b4eb255f4fa91c9c1f2068b20a2de2472967ca3d22602b"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer_config.json",
+      "bytes": 61728,
+      "sha256": "ed9a3a8b0faa71a70a32847e0435fe036e6e112d4df4edb7bb48a921e344dc05"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/model_components.json",
+      "bytes": 318,
+      "sha256": "4e31340625635eea1f0d0935e5ff1a3e47689cb38088ad40b1dcd06add1bc0c5"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/README.md",
+      "bytes": 1147,
+      "sha256": "9e230513fc75b9ca1f432d1f6ef92a7416ff2e0e02f20ef50d6bc789b6d40747"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model-00001-of-00003.safetensors",
+      "bytes": 4935827416,
+      "sha256": "19455304c63fe471f7241a6785ef804b8012edd8ce9f30c74e8825f03413c96b"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model-00002-of-00003.safetensors",
+      "bytes": 4932780944,
+      "sha256": "5cbed706d3edd448e4d32188892cd87ed8a1223207d2482d09a40ca4cfbed6ab"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model-00003-of-00003.safetensors",
+      "bytes": 1493237128,
+      "sha256": "e56bfcc518f43f1fd83727e673cc121a171594082fc9e14164179363fbccc182"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model.safetensors.index.json",
+      "bytes": 16681,
+      "sha256": "8322567493a4f08dce5d97f8621a2896a5ed1b72e0865371e3339599e077ebb2"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/reshard_manifest.json",
+      "bytes": 26445,
+      "sha256": "b2cc0414f6693d95f0486fe9cf1e60b8f9757b6a578855421c1a3bc50e14feae"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/README.md",
+      "bytes": 1172,
+      "sha256": "90bd23f138e69e6099f7634993b32ed066fe92a604b396a9387bf6d167017839"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model-00001-of-00002.safetensors",
+      "bytes": 4996788840,
+      "sha256": "3b611c672b94037e07d90c4374e5b17eea45a5abe4a090f2875b67dd120a83d2"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model-00002-of-00002.safetensors",
+      "bytes": 2149278616,
+      "sha256": "4dff7356c1b66cb9519ab669a78f46e7a03eb5aca60c3588348f5d4285495e8f"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model.safetensors.index.json",
+      "bytes": 113661,
+      "sha256": "b6e35916452ede069646051df78656ff577474db05d4bfc435b81f18fdeebb7d"
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/reshard_manifest.json",
+      "bytes": 133137,
+      "sha256": "c73909909d5241a3816896220a2b72705c0078fbf034848b154183aada36e6c8"
+    },
+    {
+      "path": "native_reader_validation.json",
+      "bytes": 3362,
+      "sha256": "7c6f40d2ae7126dd35e92e29d38bb47c459318711fdb26ba72201f5cd82fcaf7"
+    },
+    {
+      "path": "research/caption_dpo/epoch-2.safetensors",
+      "bytes": 660999900,
+      "sha256": "ff13d7f409c6392a00f3dfcb42c32fccb11c77b4ad2f721e276fe96513017bbf"
+    },
+    {
+      "path": "research/joint_branch/epoch-3.safetensors",
+      "bytes": 1416371272,
+      "sha256": "522d9ff9e721ab7ee9a7272a6dfbdf0aaedb1c6c4e8f5fa1d9b27ac73ba0fad0"
+    },
+    {
+      "path": "research/mask_predictor_paperalign/epoch-4.pt",
+      "bytes": 22230487,
+      "sha256": "4cd0d08b16782c7ca3566db23d378b206880203f013b3c017791712aa66d0704"
+    },
+    {
+      "path": "research/native_narr_dit/epoch-4.safetensors",
+      "bytes": 350032624,
+      "sha256": "a112106d5a2bd851c3a635ac752268aa8154a1eab5101d4ee762f97f64fa3b1a"
+    },
+    {
+      "path": "research/vlm_comparison/epoch-0.safetensors",
+      "bytes": 755371392,
+      "sha256": "f6abd392ec7b18e182c1e4c0e840794aa29c629036b290c013fe6ee4c0df1de4"
+    },
+    {
+      "path": "tools/attach_model_bundle.py",
+      "bytes": 4976,
+      "sha256": "02c24bf6017a2450411d6a6056b6004107b453239b3c61c5f729a6f31e84f9be"
+    },
+    {
+      "path": "tools/prepare_egoexo_model_bundle.py",
+      "bytes": 26438,
+      "sha256": "45dd80eda5ebd3a4545678a4567eb702fac1631a6a830fec07cf708c35d41a46"
+    },
+    {
+      "path": "tools/reshard_weights.py",
+      "bytes": 26525,
+      "sha256": "cab58ac00a4acda90cda76cf00cf9e3f7bb8e883b596653db6ee4efec81d7034"
+    },
+    {
+      "path": "tools/tests/test_attach_model_bundle.py",
+      "bytes": 3223,
+      "sha256": "caf3c1f8a36bd4d4fa3e4327438dc22a962cb7b43369254e235f74c926cd4832"
+    },
+    {
+      "path": "tools/tests/test_model_resources.py",
+      "bytes": 3401,
+      "sha256": "16162f1dc790a511a797a1f4b4ec9d402ea08c8579db005bee128ed5368533ce"
+    },
+    {
+      "path": "tools/tests/test_reshard_weights.py",
+      "bytes": 7738,
+      "sha256": "e16945ecb5331cc97730bc6f3a704dfc2f50e69501c61ada177d06bdce347ea9"
+    },
+    {
+      "path": "tools/verify_model_bundle.py",
+      "bytes": 1785,
+      "sha256": "c602d4305f59c388105765835b3b7d9cacf2181e8494014fea7f0dc57e728cb8"
+    }
+  ],
+  "total_file_bytes": 46092480857,
+  "largest_file_bytes": 4999831048,
+  "native_reader": "safetensors.safe_open(framework=pt, device=cpu), slices only",
+  "validation": {
+    "all_copied_weights_read_back_SHA256_verified": true,
+    "resharded_tensor_bytes_independently_SHA256_verified": true,
+    "native_reader_names_shapes_dtypes_verified": true,
+    "core_sharded_loader_paths_verified": true
+  },
+  "GPU_used": false,
+  "model_loaded": false,
+  "inference_run": false,
+  "training_run": false,
+  "upload_run": false,
+  "raw_dataset_included": false,
+  "distribution": {
+    "repo_id": "diffusion-gif/any2ego",
+    "repo_type": "model",
+    "visibility": "private",
+    "source_export_manifest_sha256": "f17006bbe222737d8dd9e4cb827bd54f090c59f02762dfef9a9c5928a1caf117",
+    "note": "Execution booleans above refer to original local export; README distribution text normalized."
+  }
+}

checkpoints/caption_grpo/adapter_config.json

@@ -0,0 +1,40 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3-VL-8B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [],
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": "^(model\\.language_model(?=\\.).*\\.(gate_proj|o_proj|down_proj|q_proj|v_proj|k_proj|up_proj))$",
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoints/caption_grpo/additional_config.json

@@ -0,0 +1,5 @@
+{
+  "lora_dtype": null,
+  "lorap_lr_ratio": null,
+  "lorap_emb_lr": 1e-06
+}

checkpoints/sft_only/adapter_config.json

@@ -0,0 +1,40 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3-VL-8B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [],
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": "^(model\\.language_model(?=\\.).*\\.(down_proj|q_proj|k_proj|o_proj|up_proj|v_proj|gate_proj))$",
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoints/sft_only/additional_config.json

@@ -0,0 +1,5 @@
+{
+  "lora_dtype": null,
+  "lorap_lr_ratio": null,
+  "lorap_emb_lr": 1e-06
+}

code_support/diffusion/infer_caption.py

@@ -0,0 +1,173 @@
+""""""
+from pathlib import Path as _Path
+import sys as _sys
+_bundle_root = _Path(__file__).resolve().parents[1]
+_sys.path.insert(0, str(_bundle_root))
+from project_paths import project_path as _project_path, env as _env, initialize as _initialize
+_initialize(__name__ == '__main__')
+from project_paths import seg_mask_root, seg_mask_dir
+import os
+import sys
+import json
+import argparse
+import numpy as np
+import torch
+from PIL import Image
+from model_resources import wan_base_root, wan_model_paths, wan_tokenizer_path
+VACE = wan_base_root()
+DS = _project_path('third_party/DiffSynth-Studio')
+HERE = os.path.dirname(os.path.abspath(__file__))
+EVAL_MANIFEST = _project_path('manifests/eval.json')
+MASK_ROOT = seg_mask_root()
+CAPTION_JSON = _project_path('data/captions/grpo.json')
+PALETTE = np.array([[0, 0, 0], [220, 40, 40], [40, 200, 80]], dtype=np.uint8)
+NEG = '色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，鱼眼畸变，鱼眼镜头，广角畸变，桶形畸变，镜头畸变，边缘拉伸变形，画面弯曲，fisheye distortion，wide-angle distortion，lens distortion，barrel distortion，可见的相机，三脚架，GoPro，运动相机'
+
+def build_pipe(device, lora_path, branch_ckpt, caption_dim=4096):
+    sys.path.insert(0, DS)
+    sys.path.insert(0, HERE)
+    from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
+    from caption_cross_attn import inject_caption_cross_attn
+    pipe = WanVideoPipeline.from_pretrained(torch_dtype=torch.bfloat16, device=device, model_configs=[ModelConfig(path=path) for path in wan_model_paths(VACE, strict=True)], tokenizer_config=ModelConfig(path=wan_tokenizer_path(VACE, strict=True)))
+    if lora_path:
+        pipe.load_lora(pipe.vace, lora_path, alpha=1.0)
+        print(f'已加载 Stage1 底座 LoRA: {lora_path}')
+    dit = pipe.dit
+    dev = next(dit.parameters()).device
+    dtype = next(dit.parameters()).dtype
+    from safetensors.torch import load_file
+    sd = load_file(branch_ckpt)
+    ckpt_has_route = any(('spatial_route' in k for k in sd.keys()))
+    env_route = os.environ.get('USE_SPATIAL_ROUTE')
+    use_spatial_route = env_route != '0' if env_route is not None else ckpt_has_route
+    inject_caption_cross_attn(dit, caption_dim=caption_dim, vace_module=pipe.vace, use_spatial_route=use_spatial_route)
+    for block in dit.blocks:
+        block.cross_attn._cap_branch.to(device=dev, dtype=dtype)
+    dit_sd = dit.state_dict()
+    n_cap = 0
+    miss = []
+    for k, v in sd.items():
+        kk = k
+        for pre in ('pipe.dit.', 'dit.', 'model.'):
+            if kk.startswith(pre):
+                kk = kk[len(pre):]
+        if kk in dit_sd:
+            dit_sd[kk].copy_(v.to(dit_sd[kk].dtype).to(dit_sd[kk].device))
+            if '_cap_branch' in kk:
+                n_cap += 1
+        else:
+            miss.append(k)
+    print(f'[caption ckpt] 加载 caption {n_cap}/{len(sd)} 个参数 <- {branch_ckpt}')
+    if miss:
+        print(f'[caption ckpt] 未匹配 {len(miss)} 个 key, 样本: {miss[:3]}')
+    for block in dit.blocks:
+        cb = block.cross_attn._cap_branch
+        cb.gate_cap.data = cb.gate_cap.data.float()
+    print(f'[caption ckpt] block0 gate_cap={dit.blocks[0].cross_attn._cap_branch.gate_cap.item():+.4e}')
+    return pipe
+
+@torch.no_grad()
+def encode_caption(pipe, cap):
+    """"""
+    if cap is None:
+        return None
+    cap = str(cap).strip()
+    if len(cap) == 0:
+        return None
+    pipe.load_models_to_device(('text_encoder',))
+    ids, mask = pipe.tokenizer(cap, return_mask=True, add_special_tokens=True)
+    ids = ids.to(pipe.device)
+    mask = mask.to(pipe.device)
+    seq_lens = mask.gt(0).sum(dim=1).long()
+    feat = pipe.text_encoder(ids, mask)
+    for i, v in enumerate(seq_lens):
+        feat[:, v:] = 0
+    return feat.to(device=pipe.device, dtype=pipe.torch_dtype)
+
+def load_mask_video(mask_dir, size):
+    """"""
+    fs = sorted((f for f in os.listdir(mask_dir) if f.endswith('.png')))
+    out = []
+    for f in fs:
+        m = np.asarray(Image.open(os.path.join(mask_dir, f)))
+        if m.ndim == 3:
+            m = m[..., 0]
+        col = PALETTE[np.clip(m, 0, 2)]
+        out.append(Image.fromarray(col).resize(size))
+    return out
+
+def main():
+    mode_parser = argparse.ArgumentParser(add_help=False)
+    modes = ['global', 'spatial']
+    mode_parser.add_argument('--variant', choices=modes, default='spatial')
+    mode, _ = mode_parser.parse_known_args()
+    branch = 'global' if mode.variant == 'global' else 'spatial'
+    ap = argparse.ArgumentParser()
+    ap.add_argument('--variant', choices=modes, default=mode.variant)
+    ap.add_argument('--lora', default=_project_path('checkpoints/generator_hoi/ckpt.safetensors'), help='Stage 1 HOI 底座，与分支训练的 preset_lora_path 一致')
+    ap.add_argument('--branch_ckpt', default=_project_path(f'checkpoints/generator_{branch}/ckpt.safetensors'))
+    ap.add_argument('--out', default=_project_path(f'outputs/pred_{mode.variant}'))
+    ap.add_argument('--manifest', default=EVAL_MANIFEST)
+    ap.add_argument('--caption_json', default=CAPTION_JSON)
+    ap.add_argument('--caption_dim', type=int, default=4096)
+    ap.add_argument('--height', type=int, default=480)
+    ap.add_argument('--width', type=int, default=480)
+    ap.add_argument('--steps', type=int, default=50)
+    ap.add_argument('--cfg_scale', type=float, default=5.0)
+    ap.add_argument('--vace_scale', type=float, default=1.0)
+    ap.add_argument('--fps', type=float, default=8.0)
+    ap.add_argument('--seed', type=int, default=0)
+    ap.add_argument('--limit', type=int, default=-1)
+    ap.add_argument('--mask_root', default=MASK_ROOT, help='外部 seg 预测 mask 根目录：<root>/<clip_id>/ego/*.png')
+    ap.add_argument('--device', default='cuda')
+    args = ap.parse_args()
+    os.environ['USE_SPATIAL_ROUTE'] = '0' if args.variant == 'global' else '1'
+    sys.path.insert(0, HERE)
+    from caption_cross_attn import set_caption_context
+    manifest = json.load(open(args.manifest))
+    if args.limit > 0:
+        manifest = manifest[:args.limit]
+    captions = json.load(open(args.caption_json))
+    out = os.path.abspath(args.out)
+    os.makedirs(out, exist_ok=True)
+    pipe = build_pipe(args.device, args.lora, args.branch_ckpt, args.caption_dim)
+    size = (args.width, args.height)
+    print(f'开始 caption 旁路推理, {len(manifest)} 条 | cfg={args.cfg_scale}')
+    n_done = 0
+    for k, s in enumerate(manifest):
+        uid = s['take_uid']
+        if os.path.isfile(os.path.join(out, uid, 'pred.mp4')):
+            print(f'  [skip] 已存在: {uid}')
+            n_done += 1
+            continue
+        mask_dir = os.path.join(args.mask_root, uid, 'ego')
+        if not os.path.isdir(mask_dir):
+            print(f'  [skip] 无mask: {s['take_name']}')
+            continue
+        cap = captions.get(uid)
+        if cap is None:
+            print(f'  [skip] 无caption: {s['take_name']}')
+            continue
+        mask_vid = load_mask_video(mask_dir, size)
+        nf = len(mask_vid)
+        ref = Image.open(s['first_frame']).convert('RGB').resize(size)
+        cap_feat = encode_caption(pipe, cap)
+        set_caption_context(pipe.dit, cap_feat)
+        cap_shape = tuple(cap_feat.shape) if cap_feat is not None else 'None(旁路关)'
+        print(f"[{k + 1}/{len(manifest)}] {s['take_name']} | {nf}帧 | variant={args.variant} | cap{cap_shape} | '{s['prompt'][:40]}'")
+        video = pipe(prompt=s['prompt'], negative_prompt=NEG, vace_video=mask_vid, vace_reference_image=ref, vace_scale=args.vace_scale, height=args.height, width=args.width, num_frames=nf, num_inference_steps=args.steps, cfg_scale=args.cfg_scale, seed=args.seed, tiled=True)
+        sd = os.path.join(out, uid)
+        os.makedirs(sd, exist_ok=True)
+        for i, fr in enumerate(video):
+            Image.fromarray(np.asarray(fr)).save(os.path.join(sd, f'{i:03d}.png'))
+        try:
+            from diffsynth.utils.data import save_video
+            save_video(video, os.path.join(sd, 'pred.mp4'), fps=args.fps, quality=5)
+        except Exception:
+            pass
+        n_done += 1
+        print(f'    -> {sd}')
+    json.dump({'model': 'Wan2.1-VACE-1.3B + HOI-LoRA + caption 旁路', 'lora': args.lora, 'branch_ckpt': args.branch_ckpt, 'caption_json': args.caption_json, 'height': args.height, 'width': args.width, 'rotate': False, 'vace_scale': args.vace_scale, 'steps': args.steps, 'cfg_scale': args.cfg_scale, 'variant': args.variant, 'seed': args.seed, 'num_samples': n_done, 'note': 'ego HOI mask + narration(原生) + ego dense caption(旁路) 引导生成'}, open(os.path.join(out, 'infer_config.json'), 'w'), ensure_ascii=False, indent=2)
+    print(f'完成 {n_done} 条 ->', out)
+if __name__ == '__main__':
+    main()

code_support/diffusion/infer_vace_hoi.py

@@ -0,0 +1,97 @@
+""""""
+from pathlib import Path as _Path
+import sys as _sys
+_bundle_root = _Path(__file__).resolve().parents[1]
+_sys.path.insert(0, str(_bundle_root))
+from project_paths import project_path as _project_path, env as _env, initialize as _initialize
+_initialize(__name__ == '__main__')
+from project_paths import seg_mask_root, seg_mask_dir
+import os
+import sys
+import json
+import argparse
+import numpy as np
+import torch
+from PIL import Image
+HERE = os.path.dirname(os.path.abspath(__file__))
+from model_resources import wan_base_root, wan_model_paths, wan_tokenizer_path
+VACE = wan_base_root()
+DS = _project_path('third_party/DiffSynth-Studio')
+EVAL_MANIFEST = _project_path('manifests/eval.json')
+MASK_ROOT = seg_mask_root()
+PALETTE = np.array([[0, 0, 0], [220, 40, 40], [40, 200, 80]], dtype=np.uint8)
+NEG = '色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景'
+
+def build_pipe(device, lora_path):
+    sys.path.insert(0, DS)
+    sys.path.insert(0, HERE)
+    from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
+    pipe = WanVideoPipeline.from_pretrained(torch_dtype=torch.bfloat16, device=device, model_configs=[ModelConfig(path=path) for path in wan_model_paths(VACE, strict=True)], tokenizer_config=ModelConfig(path=wan_tokenizer_path(VACE, strict=True)))
+    if lora_path:
+        pipe.load_lora(pipe.vace, lora_path, alpha=1.0)
+        print(f'已加载 LoRA: {lora_path}')
+    return pipe
+
+def load_mask_video(mask_dir, size):
+    """"""
+    fs = sorted((f for f in os.listdir(mask_dir) if f.endswith('.png')))
+    out = []
+    for f in fs:
+        m = np.asarray(Image.open(os.path.join(mask_dir, f)))
+        if m.ndim == 3:
+            m = m[..., 0]
+        col = PALETTE[np.clip(m, 0, 2)]
+        out.append(Image.fromarray(col).resize(size))
+    return out
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument('--lora', default=_project_path('checkpoints/generator_hoi/ckpt.safetensors'))
+    ap.add_argument('--out', default=_project_path('outputs/pred_hoi'))
+    ap.add_argument('--height', type=int, default=480)
+    ap.add_argument('--width', type=int, default=480)
+    ap.add_argument('--steps', type=int, default=50)
+    ap.add_argument('--cfg_scale', type=float, default=5.0)
+    ap.add_argument('--vace_scale', type=float, default=1.0)
+    ap.add_argument('--fps', type=float, default=8.0)
+    ap.add_argument('--seed', type=int, default=0)
+    ap.add_argument('--limit', type=int, default=-1)
+    ap.add_argument('--manifest', default=EVAL_MANIFEST)
+    ap.add_argument('--mask_root', default=MASK_ROOT, help='外部 seg 预测 mask 根目录：<root>/<clip_id>/ego/*.png')
+    ap.add_argument('--device', default='cuda')
+    args = ap.parse_args()
+    manifest = json.load(open(args.manifest))
+    if args.limit > 0:
+        manifest = manifest[:args.limit]
+    out = os.path.abspath(args.out)
+    os.makedirs(out, exist_ok=True)
+    pipe = build_pipe(args.device, args.lora)
+    size = (args.width, args.height)
+    print(f'开始 M2 推理, {len(manifest)} 条')
+    for k, s in enumerate(manifest):
+        if os.path.isfile(os.path.join(out, s['take_uid'], 'pred.mp4')):
+            print(f'  [skip] 已存在: {s['take_uid']}')
+            continue
+        mask_dir = os.path.join(args.mask_root, s['take_uid'], 'ego')
+        if not os.path.isdir(mask_dir):
+            print(f'  [skip] 无mask: {s['take_name']}')
+            continue
+        mask_vid = load_mask_video(mask_dir, size)
+        nf = len(mask_vid)
+        ref = Image.open(s['first_frame']).convert('RGB').resize(size)
+        print(f"[{k + 1}/{len(manifest)}] {s['take_name']} | {nf}帧 | '{s['prompt'][:40]}'")
+        video = pipe(prompt=s['prompt'], negative_prompt=NEG, vace_video=mask_vid, vace_reference_image=ref, vace_scale=args.vace_scale, height=args.height, width=args.width, num_frames=nf, num_inference_steps=args.steps, cfg_scale=args.cfg_scale, seed=args.seed, tiled=True)
+        sd = os.path.join(out, s['take_uid'])
+        os.makedirs(sd, exist_ok=True)
+        for i, fr in enumerate(video):
+            Image.fromarray(np.asarray(fr)).save(os.path.join(sd, f'{i:03d}.png'))
+        try:
+            from diffsynth.utils.data import save_video
+            save_video(video, os.path.join(sd, 'pred.mp4'), fps=args.fps, quality=5)
+        except Exception:
+            pass
+        print(f'    -> {sd}')
+    json.dump({'model': 'Wan2.1-VACE-1.3B + HOI-LoRA', 'lora': args.lora, 'height': args.height, 'width': args.width, 'rotate': False, 'vace_scale': args.vace_scale, 'note': 'seg 预测的 ego HOI mask 引导生成'}, open(os.path.join(out, 'infer_config.json'), 'w'), indent=2)
+    print('完成 ->', out)
+if __name__ == '__main__':
+    main()

code_support/generator_defaults.py

@@ -0,0 +1,31 @@
+"""Native Python defaults shared by generator training entries."""
+import json
+from model_resources import wan_base_root, wan_model_paths, wan_tokenizer_path
+
+
+def set_training_defaults(parser, variant):
+    model = wan_base_root()
+    data = "data/vace_train_v2"
+    caption_source = "teacher" if variant == "reward" else "grpo"
+    defaults = dict(
+        dataset_base_path=data,
+        dataset_metadata_path=f"{data}/metadata.csv" if variant == "hoi" else f"{data}/metadata_caption_branch_{caption_source}.csv",
+        data_file_keys="video,vace_video,vace_reference_image",
+        extra_inputs="vace_video,vace_reference_image",
+        height=480, width=480, num_frames=13, dataset_repeat=1, num_epochs=5,
+        model_paths=json.dumps(wan_model_paths(model)),
+        tokenizer_path=wan_tokenizer_path(model),
+        use_gradient_checkpointing_offload=True,
+        output_path=f"outputs/train_{variant}",
+        learning_rate=1e-4 if variant == "hoi" else 3e-4,
+    )
+    if variant == "hoi":
+        defaults.update(lora_base_model="vace", lora_target_modules="q,k,v,o,ffn.0,ffn.2", lora_rank=128)
+    else:
+        defaults.update(preset_lora_path="checkpoints/generator_hoi/ckpt.safetensors", preset_lora_model="vace", find_unused_parameters=True)
+    parser.set_defaults(**defaults)
+    # Upstream required options now have concrete package defaults.
+    for action in parser._actions:
+        if action.dest in defaults:
+            action.required = False
+    return parser

code_support/loader_patch.json

@@ -0,0 +1,25 @@
+{
+  "note": "Installer patches only exact known original files, never unknown local edits.",
+  "files": [
+    {
+      "path": "generator_defaults.py",
+      "previous_sha256": "f576a6ceaa29cfb78ba8d783ddadf52bffcfb5f30a8740d55f9e55af1b0a4369",
+      "new_sha256": "48195fb1515b26d0bc6440db02d3181bd1ab536143bc44b5c251c7247b2cdc4a"
+    },
+    {
+      "path": "diffusion/infer_caption.py",
+      "previous_sha256": "377b52f76012189f6ca779c645d2891a8769e160c27a11d09a5591889de93aeb",
+      "new_sha256": "c3882d05e91dd7cc4ad55d4f5d56d001c1cf028a16aa33e491a833bfb3d6583a"
+    },
+    {
+      "path": "diffusion/infer_vace_hoi.py",
+      "previous_sha256": "37e8ecb9f92551d048524226f22f4c0f86086eb69ca6e9a7bf56d69b47c955d4",
+      "new_sha256": "db5e8bfe8d5ff45e0dc29dfcbdb1bab4e70febd9d66dedc46a1f6404f73224fb"
+    },
+    {
+      "path": "model_resources.py",
+      "previous_sha256": null,
+      "new_sha256": "d7449d7c527adbe7645d1ffe1942e22cc411ad7afe59a40f652ebf5da3f1daf1"
+    }
+  ]
+}

code_support/model_resources.py

@@ -0,0 +1,70 @@
+"""Resolve original or size-bounded Wan components without importing torch.
+
+DiffSynth accepts one string or a list of shard paths per ModelConfig. Do not
+pass an index JSON to its binary loader or treat each shard as a separate model.
+WAN_MODEL_ROOT may point to an independently downloaded model bundle.
+"""
+import json
+import os
+from pathlib import Path
+from project_paths import project_path
+
+
+def wan_base_root(root=None):
+    return str(Path(root or os.environ.get('WAN_MODEL_ROOT') or
+                    project_path('models/Wan2.1-VACE-1.3B')).expanduser().resolve())
+
+
+def indexed_shards(index_path):
+    index_path = Path(index_path)
+    index = json.loads(index_path.read_text())
+    mapping = index.get('weight_map')
+    if not isinstance(mapping, dict) or not mapping:
+        raise ValueError('empty or invalid model weight index: ' + str(index_path))
+    names = set()
+    for name in mapping.values():
+        if not isinstance(name, str) or Path(name).name != name or not name.endswith('.safetensors'):
+            raise ValueError('unsafe shard path in model index')
+        names.add(name)
+    paths = [index_path.parent / name for name in sorted(names)]
+    for path in paths:
+        if not path.is_file():
+            raise FileNotFoundError('missing model shard: ' + str(path))
+    return [str(path) for path in paths]
+
+
+def component_path(root, original, indices, strict=False):
+    original_path = root / original
+    if original_path.is_file():
+        return str(original_path)
+    for name in indices:
+        index_path = root / name
+        if index_path.is_file():
+            return indexed_shards(index_path)
+    if strict:
+        raise FileNotFoundError('missing original or indexed model component: ' + str(original_path))
+    # Preserve historical command defaults when no weights are present (e.g. dry-run).
+    return str(original_path)
+
+
+def wan_model_paths(root=None, strict=False):
+    root = Path(wan_base_root(root))
+    return [
+        component_path(root, 'diffusion_pytorch_model.safetensors', (
+            'transformer/diffusion_pytorch_model.safetensors.index.json',
+            'diffusion_pytorch_model.safetensors.index.json',
+        ), strict),
+        component_path(root, 'models_t5_umt5-xxl-enc-bf16.pth', (
+            'text_encoder/model.safetensors.index.json',
+            'text_encoder/models_t5_umt5-xxl-enc-bf16.safetensors.index.json',
+            'models_t5_umt5-xxl-enc-bf16.safetensors.index.json',
+        ), strict),
+        component_path(root, 'Wan2.1_VAE.pth', (), strict),
+    ]
+
+
+def wan_tokenizer_path(root=None, strict=False):
+    path = Path(wan_base_root(root)) / 'google/umt5-xxl'
+    if strict and not (path / 'tokenizer.json').is_file() and not (path / 'spiece.model').is_file():
+        raise FileNotFoundError('missing Wan umT5 tokenizer: ' + str(path))
+    return str(path)

code_support/project_paths.py

@@ -0,0 +1,36 @@
+"""Resolve package-relative resources without machine-specific locations."""
+import os
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parent
+
+
+def env(name, default=""):
+    return os.environ.get(name, default)
+
+
+def project_path(relative):
+    path = Path(relative)
+    return str(path if path.is_absolute() else ROOT / path)
+
+
+def initialize(entrypoint=False):
+    for relative in ("eval", "diffusion", "data"):
+        location = project_path(relative)
+        if location not in sys.path:
+            sys.path.insert(0, location)
+    if entrypoint:
+        os.chdir(ROOT)
+    os.environ.setdefault("TORCH_HOME", project_path(".cache/torch"))
+
+
+
+def seg_mask_root(root=None):
+    """External PhiSeg output root; no masks are distributed with the code."""
+    return project_path(root or os.environ.get("SEG_MASK_ROOT", "data/seg_masks"))
+
+
+def seg_mask_dir(clip_id, root=None):
+    """Same layout as infer_phiseg: <root>/<clip_id>/ego/*.png."""
+    return str(Path(seg_mask_root(root)) / clip_id / "ego")

models/CLIP-ViT-H-14-laion2B-s32B-b79K/README.md

@@ -0,0 +1,12 @@
+---
+license: mit
+library_name: transformers
+pipeline_tag: zero-shot-image-classification
+---
+# CLIP ViT-H/14 base dependency for Any2Ego
+
+The original Transformers `model.safetensors` and processor/tokenizer files
+are copied unchanged and hash-verified. This is not an Any2Ego-trained model.
+The project uses `CLIPModel`/`CLIPProcessor.from_pretrained` here; redundant
+OpenCLIP/bin copies are intentionally omitted. See `UPSTREAM_README.md` for
+source model documentation and terms. losslessly prepared from local artifacts.

models/CLIP-ViT-H-14-laion2B-s32B-b79K/UPSTREAM_README.md

@@ -0,0 +1,165 @@
+---
+license: mit
+widget:
+- src: >-
+    https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
+  candidate_labels: playing music, playing sports
+  example_title: Cat & Dog
+library_name: open_clip
+pipeline_tag: zero-shot-image-classification
+---
+# Model Card for CLIP ViT-H/14 - LAION-2B
+
+#  Table of Contents
+
+1. [Model Details](#model-details)
+2. [Uses](#uses)
+3. [Training Details](#training-details)
+4. [Evaluation](#evaluation)
+5. [Acknowledgements](#acknowledgements)
+6. [Citation](#citation)
+7. [How To Get Started With the Model](#how-to-get-started-with-the-model)
+
+
+# Model Details
+
+## Model Description
+
+A CLIP ViT-H/14 model trained with the LAION-2B English subset of LAION-5B (https://laion.ai/blog/laion-5b/) using OpenCLIP (https://github.com/mlfoundations/open_clip).
+
+Model training done by Romain Beaumont on the [stability.ai](https://stability.ai/) cluster. 
+
+# Uses
+
+As per the original [OpenAI CLIP model card](https://github.com/openai/CLIP/blob/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1/model-card.md), this model is intended as a research output for research communities. We hope that this model will enable researchers to better understand and explore zero-shot, arbitrary image classification. We also hope it can be used for interdisciplinary studies of the potential impact of such model. 
+
+The OpenAI CLIP paper includes a discussion of potential downstream impacts to provide an example for this sort of analysis. Additionally, the LAION-5B blog (https://laion.ai/blog/laion-5b/) and upcoming paper include additional discussion as it relates specifically to the training dataset. 
+
+## Direct Use
+
+Zero-shot image classification, image and text retrieval, among others.
+
+## Downstream Use
+
+Image classification and other image task fine-tuning, linear probe image classification, image generation guiding and conditioning, among others.
+
+## Out-of-Scope Use
+
+As per the OpenAI models,
+
+**Any** deployed use case of the model - whether commercial or not - is currently out of scope. Non-deployed use cases such as image search in a constrained environment, are also not recommended unless there is thorough in-domain testing of the model with a specific, fixed class taxonomy. This is because our safety assessment demonstrated a high need for task specific testing especially given the variability of CLIP’s performance with different class taxonomies. This makes untested and unconstrained deployment of the model in any use case currently potentially harmful. 
+
+Certain use cases which would fall under the domain of surveillance and facial recognition are always out-of-scope regardless of performance of the model. This is because the use of artificial intelligence for tasks such as these can be premature currently given the lack of testing norms and checks to ensure its fair use.
+
+Since the model has not been purposefully trained in or evaluated on any languages other than English, its use should be limited to English language use cases.
+
+Further the above notice, the LAION-5B dataset used in training of these models has additional considerations, see below.
+
+# Training Details
+
+## Training Data
+
+This model was trained with the 2 Billion sample English subset of LAION-5B (https://laion.ai/blog/laion-5b/).
+
+**IMPORTANT NOTE:** The motivation behind dataset creation is to democratize research and experimentation around large-scale multi-modal model training and handling of uncurated, large-scale datasets crawled from publically available internet. Our recommendation is therefore to use the dataset for research purposes. Be aware that this large-scale dataset is uncurated. Keep in mind that the uncurated nature of the dataset means that collected links may lead to strongly discomforting and disturbing content for a human viewer. Therefore, please use the demo links with caution and at your own risk. It is possible to extract a “safe” subset by filtering out samples based on the safety tags (using a customized trained NSFW classifier that we built). While this strongly reduces the chance for encountering potentially harmful content when viewing, we cannot entirely exclude the possibility for harmful content being still present in safe mode, so that the warning holds also there. We think that providing the dataset openly to broad research and other interested communities will allow for transparent investigation of benefits that come along with training large-scale models as well as pitfalls and dangers that may stay unreported or unnoticed when working with closed large datasets that remain restricted to a small community. Providing our dataset openly, we however do not recommend using it for creating ready-to-go industrial products, as the basic research about general properties and safety of such large-scale models, which we would like to encourage with this release, is still in progress.
+
+## Training Procedure
+
+Please see [training notes](https://docs.google.com/document/d/1EFbMLRWSSV0LUf9Du1pWzWqgeiIRPwEWX2s1C6mAk5c) and [wandb logs](https://wandb.ai/rom1504/eval_openclip/reports/H-14--VmlldzoyNDAxODQ3).
+
+# Evaluation
+
+Evaluation done with code in the [LAION CLIP Benchmark suite](https://github.com/LAION-AI/CLIP_benchmark).
+
+## Testing Data, Factors & Metrics
+
+### Testing Data
+
+The testing is performed with VTAB+ (A combination of VTAB (https://arxiv.org/abs/1910.04867) w/ additional robustness datasets) for classification and COCO and Flickr for retrieval.
+
+**TODO** - more detail
+
+## Results
+
+The model achieves a 78.0 zero-shot top-1 accuracy on ImageNet-1k.
+
+An initial round of benchmarks have been performed on a wider range of datasets, currently viewable at https://github.com/LAION-AI/CLIP_benchmark/blob/main/benchmark/results.ipynb
+
+**TODO** - create table for just this model's metrics.
+
+# Acknowledgements
+
+Acknowledging [stability.ai](https://stability.ai/) for the compute used to train this model.
+
+# Citation
+
+**BibTeX:**
+
+LAION-5B
+```bibtex
+@inproceedings{schuhmann2022laionb,
+  title={{LAION}-5B: An open large-scale dataset for training next generation image-text models},
+  author={Christoph Schuhmann and
+          Romain Beaumont and
+          Richard Vencu and
+          Cade W Gordon and
+          Ross Wightman and
+          Mehdi Cherti and
+          Theo Coombes and
+          Aarush Katta and
+          Clayton Mullis and
+          Mitchell Wortsman and
+          Patrick Schramowski and
+          Srivatsa R Kundurthy and
+          Katherine Crowson and
+          Ludwig Schmidt and
+          Robert Kaczmarczyk and
+          Jenia Jitsev},
+  booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
+  year={2022},
+  url={https://openreview.net/forum?id=M3Y74vmsMcY}
+}
+```
+
+OpenAI CLIP paper
+```
+@inproceedings{Radford2021LearningTV,
+  title={Learning Transferable Visual Models From Natural Language Supervision},
+  author={Alec Radford and Jong Wook Kim and Chris Hallacy and A. Ramesh and Gabriel Goh and Sandhini Agarwal and Girish Sastry and Amanda Askell and Pamela Mishkin and Jack Clark and Gretchen Krueger and Ilya Sutskever},
+  booktitle={ICML},
+  year={2021}
+}
+```
+
+OpenCLIP software
+```
+@software{ilharco_gabriel_2021_5143773,
+  author       = {Ilharco, Gabriel and
+                  Wortsman, Mitchell and
+                  Wightman, Ross and
+                  Gordon, Cade and
+                  Carlini, Nicholas and
+                  Taori, Rohan and
+                  Dave, Achal and
+                  Shankar, Vaishaal and
+                  Namkoong, Hongseok and
+                  Miller, John and
+                  Hajishirzi, Hannaneh and
+                  Farhadi, Ali and
+                  Schmidt, Ludwig},
+  title        = {OpenCLIP},
+  month        = jul,
+  year         = 2021,
+  note         = {If you use this software, please cite it as below.},
+  publisher    = {Zenodo},
+  version      = {0.1},
+  doi          = {10.5281/zenodo.5143773},
+  url          = {https://doi.org/10.5281/zenodo.5143773}
+}
+```
+
+# How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+** TODO ** - Hugging Face transformers, OpenCLIP, and timm getting started snippets

models/CLIP-ViT-H-14-laion2B-s32B-b79K/config.json

@@ -0,0 +1,179 @@
+{
+  "architectures": [
+    "CLIPModel"
+  ],
+  "initializer_factor": 1.0,
+  "logit_scale_init_value": 2.6592,
+  "model_type": "clip",
+  "projection_dim": 1024,
+  "text_config": {
+    "_name_or_path": "",
+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_dropout": 0.0,
+    "bad_words_ids": null,
+    "bos_token_id": 0,
+    "chunk_size_feed_forward": 0,
+    "cross_attention_hidden_size": null,
+    "decoder_start_token_id": null,
+    "diversity_penalty": 0.0,
+    "do_sample": false,
+    "dropout": 0.0,
+    "early_stopping": false,
+    "encoder_no_repeat_ngram_size": 0,
+    "eos_token_id": 2,
+    "exponential_decay_length_penalty": null,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "gelu",
+    "hidden_size": 1024,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 4096,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "max_position_embeddings": 77,
+    "min_length": 0,
+    "model_type": "clip_text_model",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 16,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_hidden_layers": 24,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": 1,
+    "prefix": null,
+    "problem_type": null,
+    "projection_dim": 1024,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tf_legacy_loss": false,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.21.3",
+    "typical_p": 1.0,
+    "use_bfloat16": false,
+    "vocab_size": 49408
+  },
+  "text_config_dict": {
+    "hidden_act": "gelu",
+    "hidden_size": 1024,
+    "intermediate_size": 4096,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "projection_dim": 1024
+  },
+  "torch_dtype": "float32",
+  "transformers_version": null,
+  "vision_config": {
+    "_name_or_path": "",
+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_dropout": 0.0,
+    "bad_words_ids": null,
+    "bos_token_id": null,
+    "chunk_size_feed_forward": 0,
+    "cross_attention_hidden_size": null,
+    "decoder_start_token_id": null,
+    "diversity_penalty": 0.0,
+    "do_sample": false,
+    "dropout": 0.0,
+    "early_stopping": false,
+    "encoder_no_repeat_ngram_size": 0,
+    "eos_token_id": null,
+    "exponential_decay_length_penalty": null,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "gelu",
+    "hidden_size": 1280,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "image_size": 224,
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 5120,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "min_length": 0,
+    "model_type": "clip_vision_model",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 16,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_channels": 3,
+    "num_hidden_layers": 32,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": null,
+    "patch_size": 14,
+    "prefix": null,
+    "problem_type": null,
+    "projection_dim": 1024,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tf_legacy_loss": false,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.21.3",
+    "typical_p": 1.0,
+    "use_bfloat16": false
+  },
+  "vision_config_dict": {
+    "hidden_act": "gelu",
+    "hidden_size": 1280,
+    "intermediate_size": 5120,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 32,
+    "patch_size": 14,
+    "projection_dim": 1024
+  }
+}

models/CLIP-ViT-H-14-laion2B-s32B-b79K/preprocessor_config.json

@@ -0,0 +1,19 @@
+{
+  "crop_size": 224,
+  "do_center_crop": true,
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "size": 224
+}

models/CLIP-ViT-H-14-laion2B-s32B-b79K/special_tokens_map.json

@@ -0,0 +1 @@
+{"bos_token": {"content": "<|startoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": "<|endoftext|>"}

models/CLIP-ViT-H-14-laion2B-s32B-b79K/tokenizer_config.json

@@ -0,0 +1,34 @@
+{
+    "unk_token": {
+        "content": "<|endoftext|>",
+        "single_word": false,
+        "lstrip": false,
+        "rstrip": false,
+        "normalized": true,
+        "__type": "AddedToken"
+    },
+    "bos_token": {
+        "content": "<|startoftext|>",
+        "single_word": false,
+        "lstrip": false,
+        "rstrip": false,
+        "normalized": true,
+        "__type": "AddedToken"
+    },
+    "eos_token": {
+        "content": "<|endoftext|>",
+        "single_word": false,
+        "lstrip": false,
+        "rstrip": false,
+        "normalized": true,
+        "__type": "AddedToken"
+    },
+    "pad_token": "<|endoftext|>",
+    "add_prefix_space": false,
+    "errors": "replace",
+    "do_lower_case": true,
+    "name_or_path": "openai/clip-vit-base-patch32",
+    "model_max_length": 77,
+    "special_tokens_map_file": "./special_tokens_map.json",
+    "tokenizer_class": "CLIPTokenizer"
+}

models/Qwen3-VL-8B-Instruct/README.md

@@ -0,0 +1,192 @@
+---
+license: apache-2.0
+pipeline_tag: image-text-to-text
+library_name: transformers
+---
+<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
+    <img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
+</a>
+
+
+# Qwen3-VL-8B-Instruct
+
+
+Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.
+
+This generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual perception & reasoning, extended context length, enhanced spatial and video dynamics comprehension, and stronger agent interaction capabilities.
+
+Available in Dense and MoE architectures that scale from edge to cloud, with Instruct and reasoning‑enhanced Thinking editions for flexible, on‑demand deployment.
+
+
+#### Key Enhancements:
+
+* **Visual Agent**: Operates PC/mobile GUIs—recognizes elements, understands functions, invokes tools, completes tasks.
+
+* **Visual Coding Boost**: Generates Draw.io/HTML/CSS/JS from images/videos.
+
+* **Advanced Spatial Perception**: Judges object positions, viewpoints, and occlusions; provides stronger 2D grounding and enables 3D grounding for spatial reasoning and embodied AI.
+
+* **Long Context & Video Understanding**: Native 256K context, expandable to 1M; handles books and hours-long video with full recall and second-level indexing.
+
+* **Enhanced Multimodal Reasoning**: Excels in STEM/Math—causal analysis and logical, evidence-based answers.
+
+* **Upgraded Visual Recognition**: Broader, higher-quality pretraining is able to “recognize everything”—celebrities, anime, products, landmarks, flora/fauna, etc.
+
+* **Expanded OCR**: Supports 32 languages (up from 19); robust in low light, blur, and tilt; better with rare/ancient characters and jargon; improved long-document structure parsing.
+
+* **Text Understanding on par with pure LLMs**: Seamless text–vision fusion for lossless, unified comprehension.
+
+
+#### Model Architecture Updates:
+
+<p align="center">
+    <img src="https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3-VL/qwen3vl_arc.jpg" width="80%"/>
+<p>
+
+
+1. **Interleaved-MRoPE**: Full‑frequency allocation over time, width, and height via robust positional embeddings, enhancing long‑horizon video reasoning.
+
+2. **DeepStack**: Fuses multi‑level ViT features to capture fine‑grained details and sharpen image–text alignment.
+
+3. **Text–Timestamp Alignment:** Moves beyond T‑RoPE to precise, timestamp‑grounded event localization for stronger video temporal modeling.
+
+This is the weight repository for Qwen3-VL-8B-Instruct.
+
+
+---
+
+## Model Performance
+
+**Multimodal performance**
+
+![](https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3-VL/qwen3vl_4b_8b_vl_instruct.jpg)
+
+**Pure text performance**
+![](https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3-VL/qwen3vl_4b_8b_text_instruct.jpg)
+
+## Quickstart
+
+Below, we provide simple examples to show how to use Qwen3-VL with 🤖 ModelScope and 🤗 Transformers.
+
+The code of Qwen3-VL has been in the latest Hugging Face transformers and we advise you to build from source with command:
+```
+pip install git+https://github.com/huggingface/transformers
+# pip install transformers==4.57.0 # currently, V4.57.0 is not released
+```
+
+### Using 🤗 Transformers to Chat
+
+Here we show a code snippet to show how to use the chat model with `transformers`:
+
+```python
+from transformers import Qwen3VLForConditionalGeneration, AutoProcessor
+
+# default: Load the model on the available device(s)
+model = Qwen3VLForConditionalGeneration.from_pretrained(
+    "Qwen/Qwen3-VL-8B-Instruct", dtype="auto", device_map="auto"
+)
+
+# We recommend enabling flash_attention_2 for better acceleration and memory saving, especially in multi-image and video scenarios.
+# model = Qwen3VLForConditionalGeneration.from_pretrained(
+#     "Qwen/Qwen3-VL-8B-Instruct",
+#     dtype=torch.bfloat16,
+#     attn_implementation="flash_attention_2",
+#     device_map="auto",
+# )
+
+processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
+            },
+            {"type": "text", "text": "Describe this image."},
+        ],
+    }
+]
+
+# Preparation for inference
+inputs = processor.apply_chat_template(
+    messages,
+    tokenize=True,
+    add_generation_prompt=True,
+    return_dict=True,
+    return_tensors="pt"
+)
+inputs = inputs.to(model.device)
+
+# Inference: Generation of the output
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [
+    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+]
+output_text = processor.batch_decode(
+    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+)
+print(output_text)
+```
+
+### Generation Hyperparameters
+#### VL
+```bash
+export greedy='false'
+export top_p=0.8
+export top_k=20
+export temperature=0.7
+export repetition_penalty=1.0
+export presence_penalty=1.5
+export out_seq_length=16384
+```
+
+#### Text
+```bash
+export greedy='false'
+export top_p=1.0
+export top_k=40
+export repetition_penalty=1.0
+export presence_penalty=2.0
+export temperature=1.0
+export out_seq_length=32768
+```
+
+
+## Citation
+
+If you find our work helpful, feel free to give us a cite.
+
+```
+@misc{qwen3technicalreport,
+      title={Qwen3 Technical Report}, 
+      author={Qwen Team},
+      year={2025},
+      eprint={2505.09388},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2505.09388}, 
+}
+
+@article{Qwen2.5-VL,
+  title={Qwen2.5-VL Technical Report},
+  author={Bai, Shuai and Chen, Keqin and Liu, Xuejing and Wang, Jialin and Ge, Wenbin and Song, Sibo and Dang, Kai and Wang, Peng and Wang, Shijie and Tang, Jun and Zhong, Humen and Zhu, Yuanzhi and Yang, Mingkun and Li, Zhaohai and Wan, Jianqiang and Wang, Pengfei and Ding, Wei and Fu, Zheren and Xu, Yiheng and Ye, Jiabo and Zhang, Xi and Xie, Tianbao and Cheng, Zesen and Zhang, Hang and Yang, Zhibo and Xu, Haiyang and Lin, Junyang},
+  journal={arXiv preprint arXiv:2502.13923},
+  year={2025}
+}
+
+@article{Qwen2VL,
+  title={Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution},
+  author={Wang, Peng and Bai, Shuai and Tan, Sinan and Wang, Shijie and Fan, Zhihao and Bai, Jinze and Chen, Keqin and Liu, Xuejing and Wang, Jialin and Ge, Wenbin and Fan, Yang and Dang, Kai and Du, Mengfei and Ren, Xuancheng and Men, Rui and Liu, Dayiheng and Zhou, Chang and Zhou, Jingren and Lin, Junyang},
+  journal={arXiv preprint arXiv:2409.12191},
+  year={2024}
+}
+
+@article{Qwen-VL,
+  title={Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond},
+  author={Bai, Jinze and Bai, Shuai and Yang, Shusheng and Wang, Shijie and Tan, Sinan and Wang, Peng and Lin, Junyang and Zhou, Chang and Zhou, Jingren},
+  journal={arXiv preprint arXiv:2308.12966},
+  year={2023}
+}
+```

models/Qwen3-VL-8B-Instruct/chat_template.json

@@ -0,0 +1,3 @@
+{
+    "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' }}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- for message in messages %}\n    {%- if message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content_item in message.content %}\n                {%- if 'text' in content_item %}\n                    {{- content_item.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and message.content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
+}

models/Qwen3-VL-8B-Instruct/config.json

@@ -0,0 +1,62 @@
+{
+  "architectures": [
+    "Qwen3VLForConditionalGeneration"
+  ],
+  "image_token_id": 151655,
+  "model_type": "qwen3_vl",
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "max_position_embeddings": 262144,
+    "model_type": "qwen3_vl_text",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 36,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        24,
+        20,
+        20
+      ],
+      "rope_type": "default"
+    },
+    "rope_theta": 5000000,
+    "use_cache": true,
+    "vocab_size": 151936
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.0.dev0",
+  "video_token_id": 151656,
+  "vision_config": {
+    "deepstack_visual_indexes": [
+      8,
+      16,
+      24
+    ],
+    "depth": 27,
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 4304,
+    "model_type": "qwen3_vl",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 4096,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 151653,
+  "vision_start_token_id": 151652
+}

models/Qwen3-VL-8B-Instruct/generation_config.json

@@ -0,0 +1,14 @@
+{
+    "bos_token_id": 151643,
+    "pad_token_id": 151643,
+    "do_sample": true,
+    "eos_token_id": [
+        151645,
+        151643
+    ],
+    "top_k": 20,
+    "top_p": 0.8,
+    "repetition_penalty": 1.0,
+    "temperature": 0.7,
+    "transformers_version": "4.56.0"
+}

models/Qwen3-VL-8B-Instruct/model.safetensors.index.json

@@ -0,0 +1,757 @@
+{
+  "metadata": {
+    "total_size": 17534247392
+  },
+  "weight_map": {
+    "lm_head.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.embed_tokens.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.10.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.11.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.12.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.13.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.14.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.15.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.16.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.17.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.18.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.19.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.20.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.20.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.21.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.22.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.self_attn.k_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.self_attn.q_norm.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.22.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.23.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.24.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.25.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.26.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.27.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.28.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.29.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.30.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.30.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.31.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.32.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.33.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.self_attn.k_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.self_attn.q_norm.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.34.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.35.input_layernorm.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.self_attn.k_norm.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.35.self_attn.q_norm.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.35.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "model.language_model.layers.35.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
+    "model.language_model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.6.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.9.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.language_model.layers.9.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.self_attn.k_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.self_attn.q_norm.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.layers.9.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "model.language_model.norm.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.0.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.1.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.10.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.11.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.12.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.13.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.14.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.15.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.16.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.17.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.18.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.19.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.2.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.20.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.21.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.22.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.23.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.24.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.25.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.26.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.3.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.4.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.5.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.6.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.7.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.8.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.attn.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.attn.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.attn.qkv.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.attn.qkv.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.mlp.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.mlp.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.mlp.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.mlp.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.norm1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.norm1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.norm2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.blocks.9.norm2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.0.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.0.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.0.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.0.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.0.norm.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.0.norm.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.1.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.1.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.1.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.1.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.1.norm.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.1.norm.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.2.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.2.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.2.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.2.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.2.norm.bias": "model-00004-of-00004.safetensors",
+    "model.visual.deepstack_merger_list.2.norm.weight": "model-00004-of-00004.safetensors",
+    "model.visual.merger.linear_fc1.bias": "model-00004-of-00004.safetensors",
+    "model.visual.merger.linear_fc1.weight": "model-00004-of-00004.safetensors",
+    "model.visual.merger.linear_fc2.bias": "model-00004-of-00004.safetensors",
+    "model.visual.merger.linear_fc2.weight": "model-00004-of-00004.safetensors",
+    "model.visual.merger.norm.bias": "model-00004-of-00004.safetensors",
+    "model.visual.merger.norm.weight": "model-00004-of-00004.safetensors",
+    "model.visual.patch_embed.proj.bias": "model-00004-of-00004.safetensors",
+    "model.visual.patch_embed.proj.weight": "model-00004-of-00004.safetensors",
+    "model.visual.pos_embed.weight": "model-00004-of-00004.safetensors"
+  }
+}

models/Qwen3-VL-8B-Instruct/preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

models/Qwen3-VL-8B-Instruct/tokenizer_config.json

@@ -0,0 +1,239 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' }}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- for message in messages %}\n    {%- if message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content_item in message.content %}\n                {%- if 'text' in content_item %}\n                    {{- content_item.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and message.content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 262144,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

models/Qwen3-VL-8B-Instruct/video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}

models/Wan2.1-VACE-1.3B/LICENSE.txt

@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

models/Wan2.1-VACE-1.3B/README.md

@@ -0,0 +1,7 @@
+# Wan2.1-VACE-1.3B base dependency (native DiffSynth keys)
+
+Upstream: Wan-AI/Wan2.1-VACE-1.3B, original LICENSE.txt included. Not trained
+Any2Ego branches. Native DiT/VACE is in transformer/; native BF16 umT5 is in
+text_encoder/. Supply shard lists to separate ModelConfig objects. VAE and
+umt5 tokenizer stay unchanged. See the parent README/code_support for loading.
+This is not a diffusers/Transformers architecture conversion; see the private parent repository for distribution.

models/Wan2.1-VACE-1.3B/config.json

@@ -0,0 +1,16 @@
+{
+  "_class_name": "VaceWanModel",
+  "_diffusers_version": "0.30.0",
+  "dim": 1536,
+  "eps": 1e-06,
+  "ffn_dim": 8960,
+  "freq_dim": 256,
+  "in_dim": 16,
+  "model_type": "vace",
+  "num_heads": 12,
+  "num_layers": 30,
+  "out_dim": 16,
+  "text_len": 512,
+  "vace_layers": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28],
+  "vace_in_dim": 96
+}

models/Wan2.1-VACE-1.3B/google/umt5-xxl/special_tokens_map.json

@@ -0,0 +1,308 @@
+{
+  "additional_special_tokens": [
+    "<extra_id_0>",
+    "<extra_id_1>",
+    "<extra_id_2>",
+    "<extra_id_3>",
+    "<extra_id_4>",
+    "<extra_id_5>",
+    "<extra_id_6>",
+    "<extra_id_7>",
+    "<extra_id_8>",
+    "<extra_id_9>",
+    "<extra_id_10>",
+    "<extra_id_11>",
+    "<extra_id_12>",
+    "<extra_id_13>",
+    "<extra_id_14>",
+    "<extra_id_15>",
+    "<extra_id_16>",
+    "<extra_id_17>",
+    "<extra_id_18>",
+    "<extra_id_19>",
+    "<extra_id_20>",
+    "<extra_id_21>",
+    "<extra_id_22>",
+    "<extra_id_23>",
+    "<extra_id_24>",
+    "<extra_id_25>",
+    "<extra_id_26>",
+    "<extra_id_27>",
+    "<extra_id_28>",
+    "<extra_id_29>",
+    "<extra_id_30>",
+    "<extra_id_31>",
+    "<extra_id_32>",
+    "<extra_id_33>",
+    "<extra_id_34>",
+    "<extra_id_35>",
+    "<extra_id_36>",
+    "<extra_id_37>",
+    "<extra_id_38>",
+    "<extra_id_39>",
+    "<extra_id_40>",
+    "<extra_id_41>",
+    "<extra_id_42>",
+    "<extra_id_43>",
+    "<extra_id_44>",
+    "<extra_id_45>",
+    "<extra_id_46>",
+    "<extra_id_47>",
+    "<extra_id_48>",
+    "<extra_id_49>",
+    "<extra_id_50>",
+    "<extra_id_51>",
+    "<extra_id_52>",
+    "<extra_id_53>",
+    "<extra_id_54>",
+    "<extra_id_55>",
+    "<extra_id_56>",
+    "<extra_id_57>",
+    "<extra_id_58>",
+    "<extra_id_59>",
+    "<extra_id_60>",
+    "<extra_id_61>",
+    "<extra_id_62>",
+    "<extra_id_63>",
+    "<extra_id_64>",
+    "<extra_id_65>",
+    "<extra_id_66>",
+    "<extra_id_67>",
+    "<extra_id_68>",
+    "<extra_id_69>",
+    "<extra_id_70>",
+    "<extra_id_71>",
+    "<extra_id_72>",
+    "<extra_id_73>",
+    "<extra_id_74>",
+    "<extra_id_75>",
+    "<extra_id_76>",
+    "<extra_id_77>",
+    "<extra_id_78>",
+    "<extra_id_79>",
+    "<extra_id_80>",
+    "<extra_id_81>",
+    "<extra_id_82>",
+    "<extra_id_83>",
+    "<extra_id_84>",
+    "<extra_id_85>",
+    "<extra_id_86>",
+    "<extra_id_87>",
+    "<extra_id_88>",
+    "<extra_id_89>",
+    "<extra_id_90>",
+    "<extra_id_91>",
+    "<extra_id_92>",
+    "<extra_id_93>",
+    "<extra_id_94>",
+    "<extra_id_95>",
+    "<extra_id_96>",
+    "<extra_id_97>",
+    "<extra_id_98>",
+    "<extra_id_99>",
+    "<extra_id_100>",
+    "<extra_id_101>",
+    "<extra_id_102>",
+    "<extra_id_103>",
+    "<extra_id_104>",
+    "<extra_id_105>",
+    "<extra_id_106>",
+    "<extra_id_107>",
+    "<extra_id_108>",
+    "<extra_id_109>",
+    "<extra_id_110>",
+    "<extra_id_111>",
+    "<extra_id_112>",
+    "<extra_id_113>",
+    "<extra_id_114>",
+    "<extra_id_115>",
+    "<extra_id_116>",
+    "<extra_id_117>",
+    "<extra_id_118>",
+    "<extra_id_119>",
+    "<extra_id_120>",
+    "<extra_id_121>",
+    "<extra_id_122>",
+    "<extra_id_123>",
+    "<extra_id_124>",
+    "<extra_id_125>",
+    "<extra_id_126>",
+    "<extra_id_127>",
+    "<extra_id_128>",
+    "<extra_id_129>",
+    "<extra_id_130>",
+    "<extra_id_131>",
+    "<extra_id_132>",
+    "<extra_id_133>",
+    "<extra_id_134>",
+    "<extra_id_135>",
+    "<extra_id_136>",
+    "<extra_id_137>",
+    "<extra_id_138>",
+    "<extra_id_139>",
+    "<extra_id_140>",
+    "<extra_id_141>",
+    "<extra_id_142>",
+    "<extra_id_143>",
+    "<extra_id_144>",
+    "<extra_id_145>",
+    "<extra_id_146>",
+    "<extra_id_147>",
+    "<extra_id_148>",
+    "<extra_id_149>",
+    "<extra_id_150>",
+    "<extra_id_151>",
+    "<extra_id_152>",
+    "<extra_id_153>",
+    "<extra_id_154>",
+    "<extra_id_155>",
+    "<extra_id_156>",
+    "<extra_id_157>",
+    "<extra_id_158>",
+    "<extra_id_159>",
+    "<extra_id_160>",
+    "<extra_id_161>",
+    "<extra_id_162>",
+    "<extra_id_163>",
+    "<extra_id_164>",
+    "<extra_id_165>",
+    "<extra_id_166>",
+    "<extra_id_167>",
+    "<extra_id_168>",
+    "<extra_id_169>",
+    "<extra_id_170>",
+    "<extra_id_171>",
+    "<extra_id_172>",
+    "<extra_id_173>",
+    "<extra_id_174>",
+    "<extra_id_175>",
+    "<extra_id_176>",
+    "<extra_id_177>",
+    "<extra_id_178>",
+    "<extra_id_179>",
+    "<extra_id_180>",
+    "<extra_id_181>",
+    "<extra_id_182>",
+    "<extra_id_183>",
+    "<extra_id_184>",
+    "<extra_id_185>",
+    "<extra_id_186>",
+    "<extra_id_187>",
+    "<extra_id_188>",
+    "<extra_id_189>",
+    "<extra_id_190>",
+    "<extra_id_191>",
+    "<extra_id_192>",
+    "<extra_id_193>",
+    "<extra_id_194>",
+    "<extra_id_195>",
+    "<extra_id_196>",
+    "<extra_id_197>",
+    "<extra_id_198>",
+    "<extra_id_199>",
+    "<extra_id_200>",
+    "<extra_id_201>",
+    "<extra_id_202>",
+    "<extra_id_203>",
+    "<extra_id_204>",
+    "<extra_id_205>",
+    "<extra_id_206>",
+    "<extra_id_207>",
+    "<extra_id_208>",
+    "<extra_id_209>",
+    "<extra_id_210>",
+    "<extra_id_211>",
+    "<extra_id_212>",
+    "<extra_id_213>",
+    "<extra_id_214>",
+    "<extra_id_215>",
+    "<extra_id_216>",
+    "<extra_id_217>",
+    "<extra_id_218>",
+    "<extra_id_219>",
+    "<extra_id_220>",
+    "<extra_id_221>",
+    "<extra_id_222>",
+    "<extra_id_223>",
+    "<extra_id_224>",
+    "<extra_id_225>",
+    "<extra_id_226>",
+    "<extra_id_227>",
+    "<extra_id_228>",
+    "<extra_id_229>",
+    "<extra_id_230>",
+    "<extra_id_231>",
+    "<extra_id_232>",
+    "<extra_id_233>",
+    "<extra_id_234>",
+    "<extra_id_235>",
+    "<extra_id_236>",
+    "<extra_id_237>",
+    "<extra_id_238>",
+    "<extra_id_239>",
+    "<extra_id_240>",
+    "<extra_id_241>",
+    "<extra_id_242>",
+    "<extra_id_243>",
+    "<extra_id_244>",
+    "<extra_id_245>",
+    "<extra_id_246>",
+    "<extra_id_247>",
+    "<extra_id_248>",
+    "<extra_id_249>",
+    "<extra_id_250>",
+    "<extra_id_251>",
+    "<extra_id_252>",
+    "<extra_id_253>",
+    "<extra_id_254>",
+    "<extra_id_255>",
+    "<extra_id_256>",
+    "<extra_id_257>",
+    "<extra_id_258>",
+    "<extra_id_259>",
+    "<extra_id_260>",
+    "<extra_id_261>",
+    "<extra_id_262>",
+    "<extra_id_263>",
+    "<extra_id_264>",
+    "<extra_id_265>",
+    "<extra_id_266>",
+    "<extra_id_267>",
+    "<extra_id_268>",
+    "<extra_id_269>",
+    "<extra_id_270>",
+    "<extra_id_271>",
+    "<extra_id_272>",
+    "<extra_id_273>",
+    "<extra_id_274>",
+    "<extra_id_275>",
+    "<extra_id_276>",
+    "<extra_id_277>",
+    "<extra_id_278>",
+    "<extra_id_279>",
+    "<extra_id_280>",
+    "<extra_id_281>",
+    "<extra_id_282>",
+    "<extra_id_283>",
+    "<extra_id_284>",
+    "<extra_id_285>",
+    "<extra_id_286>",
+    "<extra_id_287>",
+    "<extra_id_288>",
+    "<extra_id_289>",
+    "<extra_id_290>",
+    "<extra_id_291>",
+    "<extra_id_292>",
+    "<extra_id_293>",
+    "<extra_id_294>",
+    "<extra_id_295>",
+    "<extra_id_296>",
+    "<extra_id_297>",
+    "<extra_id_298>",
+    "<extra_id_299>"
+  ],
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "pad_token": "<pad>",
+  "unk_token": "<unk>"
+}

models/Wan2.1-VACE-1.3B/google/umt5-xxl/spiece.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e3909a67b780650b35cf529ac782ad2b6b26e6d1f849d3fbb6a872905f452458
+size 4548313

models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6e197b4d3dbd71da14b4eb255f4fa91c9c1f2068b20a2de2472967ca3d22602b
+size 16837417

models/Wan2.1-VACE-1.3B/google/umt5-xxl/tokenizer_config.json

@@ -0,0 +1,2748 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256000": {
+      "content": "<extra_id_299>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256001": {
+      "content": "<extra_id_298>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256002": {
+      "content": "<extra_id_297>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256003": {
+      "content": "<extra_id_296>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256004": {
+      "content": "<extra_id_295>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256005": {
+      "content": "<extra_id_294>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256006": {
+      "content": "<extra_id_293>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256007": {
+      "content": "<extra_id_292>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256008": {
+      "content": "<extra_id_291>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256009": {
+      "content": "<extra_id_290>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256010": {
+      "content": "<extra_id_289>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256011": {
+      "content": "<extra_id_288>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256012": {
+      "content": "<extra_id_287>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256013": {
+      "content": "<extra_id_286>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256014": {
+      "content": "<extra_id_285>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256015": {
+      "content": "<extra_id_284>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256016": {
+      "content": "<extra_id_283>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256017": {
+      "content": "<extra_id_282>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256018": {
+      "content": "<extra_id_281>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256019": {
+      "content": "<extra_id_280>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256020": {
+      "content": "<extra_id_279>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256021": {
+      "content": "<extra_id_278>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256022": {
+      "content": "<extra_id_277>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256023": {
+      "content": "<extra_id_276>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256024": {
+      "content": "<extra_id_275>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256025": {
+      "content": "<extra_id_274>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256026": {
+      "content": "<extra_id_273>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256027": {
+      "content": "<extra_id_272>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256028": {
+      "content": "<extra_id_271>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256029": {
+      "content": "<extra_id_270>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256030": {
+      "content": "<extra_id_269>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256031": {
+      "content": "<extra_id_268>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256032": {
+      "content": "<extra_id_267>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256033": {
+      "content": "<extra_id_266>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256034": {
+      "content": "<extra_id_265>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256035": {
+      "content": "<extra_id_264>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256036": {
+      "content": "<extra_id_263>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256037": {
+      "content": "<extra_id_262>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256038": {
+      "content": "<extra_id_261>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256039": {
+      "content": "<extra_id_260>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256040": {
+      "content": "<extra_id_259>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256041": {
+      "content": "<extra_id_258>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256042": {
+      "content": "<extra_id_257>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256043": {
+      "content": "<extra_id_256>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256044": {
+      "content": "<extra_id_255>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256045": {
+      "content": "<extra_id_254>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256046": {
+      "content": "<extra_id_253>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256047": {
+      "content": "<extra_id_252>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256048": {
+      "content": "<extra_id_251>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256049": {
+      "content": "<extra_id_250>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256050": {
+      "content": "<extra_id_249>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256051": {
+      "content": "<extra_id_248>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256052": {
+      "content": "<extra_id_247>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256053": {
+      "content": "<extra_id_246>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256054": {
+      "content": "<extra_id_245>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256055": {
+      "content": "<extra_id_244>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256056": {
+      "content": "<extra_id_243>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256057": {
+      "content": "<extra_id_242>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256058": {
+      "content": "<extra_id_241>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256059": {
+      "content": "<extra_id_240>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256060": {
+      "content": "<extra_id_239>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256061": {
+      "content": "<extra_id_238>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256062": {
+      "content": "<extra_id_237>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256063": {
+      "content": "<extra_id_236>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256064": {
+      "content": "<extra_id_235>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256065": {
+      "content": "<extra_id_234>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256066": {
+      "content": "<extra_id_233>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256067": {
+      "content": "<extra_id_232>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256068": {
+      "content": "<extra_id_231>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256069": {
+      "content": "<extra_id_230>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256070": {
+      "content": "<extra_id_229>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256071": {
+      "content": "<extra_id_228>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256072": {
+      "content": "<extra_id_227>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256073": {
+      "content": "<extra_id_226>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256074": {
+      "content": "<extra_id_225>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256075": {
+      "content": "<extra_id_224>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256076": {
+      "content": "<extra_id_223>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256077": {
+      "content": "<extra_id_222>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256078": {
+      "content": "<extra_id_221>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256079": {
+      "content": "<extra_id_220>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256080": {
+      "content": "<extra_id_219>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256081": {
+      "content": "<extra_id_218>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256082": {
+      "content": "<extra_id_217>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256083": {
+      "content": "<extra_id_216>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256084": {
+      "content": "<extra_id_215>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256085": {
+      "content": "<extra_id_214>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256086": {
+      "content": "<extra_id_213>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256087": {
+      "content": "<extra_id_212>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256088": {
+      "content": "<extra_id_211>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256089": {
+      "content": "<extra_id_210>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256090": {
+      "content": "<extra_id_209>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256091": {
+      "content": "<extra_id_208>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256092": {
+      "content": "<extra_id_207>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256093": {
+      "content": "<extra_id_206>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256094": {
+      "content": "<extra_id_205>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256095": {
+      "content": "<extra_id_204>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256096": {
+      "content": "<extra_id_203>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256097": {
+      "content": "<extra_id_202>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256098": {
+      "content": "<extra_id_201>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256099": {
+      "content": "<extra_id_200>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256100": {
+      "content": "<extra_id_199>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256101": {
+      "content": "<extra_id_198>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256102": {
+      "content": "<extra_id_197>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256103": {
+      "content": "<extra_id_196>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256104": {
+      "content": "<extra_id_195>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256105": {
+      "content": "<extra_id_194>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256106": {
+      "content": "<extra_id_193>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256107": {
+      "content": "<extra_id_192>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256108": {
+      "content": "<extra_id_191>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256109": {
+      "content": "<extra_id_190>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256110": {
+      "content": "<extra_id_189>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256111": {
+      "content": "<extra_id_188>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256112": {
+      "content": "<extra_id_187>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256113": {
+      "content": "<extra_id_186>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256114": {
+      "content": "<extra_id_185>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256115": {
+      "content": "<extra_id_184>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256116": {
+      "content": "<extra_id_183>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256117": {
+      "content": "<extra_id_182>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256118": {
+      "content": "<extra_id_181>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256119": {
+      "content": "<extra_id_180>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256120": {
+      "content": "<extra_id_179>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256121": {
+      "content": "<extra_id_178>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256122": {
+      "content": "<extra_id_177>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256123": {
+      "content": "<extra_id_176>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256124": {
+      "content": "<extra_id_175>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256125": {
+      "content": "<extra_id_174>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256126": {
+      "content": "<extra_id_173>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256127": {
+      "content": "<extra_id_172>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256128": {
+      "content": "<extra_id_171>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256129": {
+      "content": "<extra_id_170>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256130": {
+      "content": "<extra_id_169>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256131": {
+      "content": "<extra_id_168>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256132": {
+      "content": "<extra_id_167>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256133": {
+      "content": "<extra_id_166>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256134": {
+      "content": "<extra_id_165>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256135": {
+      "content": "<extra_id_164>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256136": {
+      "content": "<extra_id_163>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256137": {
+      "content": "<extra_id_162>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256138": {
+      "content": "<extra_id_161>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256139": {
+      "content": "<extra_id_160>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256140": {
+      "content": "<extra_id_159>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256141": {
+      "content": "<extra_id_158>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256142": {
+      "content": "<extra_id_157>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256143": {
+      "content": "<extra_id_156>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256144": {
+      "content": "<extra_id_155>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256145": {
+      "content": "<extra_id_154>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256146": {
+      "content": "<extra_id_153>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256147": {
+      "content": "<extra_id_152>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256148": {
+      "content": "<extra_id_151>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256149": {
+      "content": "<extra_id_150>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256150": {
+      "content": "<extra_id_149>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256151": {
+      "content": "<extra_id_148>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256152": {
+      "content": "<extra_id_147>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256153": {
+      "content": "<extra_id_146>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256154": {
+      "content": "<extra_id_145>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256155": {
+      "content": "<extra_id_144>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256156": {
+      "content": "<extra_id_143>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256157": {
+      "content": "<extra_id_142>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256158": {
+      "content": "<extra_id_141>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256159": {
+      "content": "<extra_id_140>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256160": {
+      "content": "<extra_id_139>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256161": {
+      "content": "<extra_id_138>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256162": {
+      "content": "<extra_id_137>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256163": {
+      "content": "<extra_id_136>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256164": {
+      "content": "<extra_id_135>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256165": {
+      "content": "<extra_id_134>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256166": {
+      "content": "<extra_id_133>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256167": {
+      "content": "<extra_id_132>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256168": {
+      "content": "<extra_id_131>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256169": {
+      "content": "<extra_id_130>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256170": {
+      "content": "<extra_id_129>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256171": {
+      "content": "<extra_id_128>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256172": {
+      "content": "<extra_id_127>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256173": {
+      "content": "<extra_id_126>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256174": {
+      "content": "<extra_id_125>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256175": {
+      "content": "<extra_id_124>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256176": {
+      "content": "<extra_id_123>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256177": {
+      "content": "<extra_id_122>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256178": {
+      "content": "<extra_id_121>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256179": {
+      "content": "<extra_id_120>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256180": {
+      "content": "<extra_id_119>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256181": {
+      "content": "<extra_id_118>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256182": {
+      "content": "<extra_id_117>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256183": {
+      "content": "<extra_id_116>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256184": {
+      "content": "<extra_id_115>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256185": {
+      "content": "<extra_id_114>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256186": {
+      "content": "<extra_id_113>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256187": {
+      "content": "<extra_id_112>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256188": {
+      "content": "<extra_id_111>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256189": {
+      "content": "<extra_id_110>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256190": {
+      "content": "<extra_id_109>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256191": {
+      "content": "<extra_id_108>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256192": {
+      "content": "<extra_id_107>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256193": {
+      "content": "<extra_id_106>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256194": {
+      "content": "<extra_id_105>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256195": {
+      "content": "<extra_id_104>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256196": {
+      "content": "<extra_id_103>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256197": {
+      "content": "<extra_id_102>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256198": {
+      "content": "<extra_id_101>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256199": {
+      "content": "<extra_id_100>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256200": {
+      "content": "<extra_id_99>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256201": {
+      "content": "<extra_id_98>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256202": {
+      "content": "<extra_id_97>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256203": {
+      "content": "<extra_id_96>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256204": {
+      "content": "<extra_id_95>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256205": {
+      "content": "<extra_id_94>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256206": {
+      "content": "<extra_id_93>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256207": {
+      "content": "<extra_id_92>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256208": {
+      "content": "<extra_id_91>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256209": {
+      "content": "<extra_id_90>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256210": {
+      "content": "<extra_id_89>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256211": {
+      "content": "<extra_id_88>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256212": {
+      "content": "<extra_id_87>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256213": {
+      "content": "<extra_id_86>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256214": {
+      "content": "<extra_id_85>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256215": {
+      "content": "<extra_id_84>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256216": {
+      "content": "<extra_id_83>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256217": {
+      "content": "<extra_id_82>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256218": {
+      "content": "<extra_id_81>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256219": {
+      "content": "<extra_id_80>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256220": {
+      "content": "<extra_id_79>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256221": {
+      "content": "<extra_id_78>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256222": {
+      "content": "<extra_id_77>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256223": {
+      "content": "<extra_id_76>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256224": {
+      "content": "<extra_id_75>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256225": {
+      "content": "<extra_id_74>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256226": {
+      "content": "<extra_id_73>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256227": {
+      "content": "<extra_id_72>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256228": {
+      "content": "<extra_id_71>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256229": {
+      "content": "<extra_id_70>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256230": {
+      "content": "<extra_id_69>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256231": {
+      "content": "<extra_id_68>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256232": {
+      "content": "<extra_id_67>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256233": {
+      "content": "<extra_id_66>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256234": {
+      "content": "<extra_id_65>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256235": {
+      "content": "<extra_id_64>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256236": {
+      "content": "<extra_id_63>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256237": {
+      "content": "<extra_id_62>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256238": {
+      "content": "<extra_id_61>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256239": {
+      "content": "<extra_id_60>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256240": {
+      "content": "<extra_id_59>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256241": {
+      "content": "<extra_id_58>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256242": {
+      "content": "<extra_id_57>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256243": {
+      "content": "<extra_id_56>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256244": {
+      "content": "<extra_id_55>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256245": {
+      "content": "<extra_id_54>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256246": {
+      "content": "<extra_id_53>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256247": {
+      "content": "<extra_id_52>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256248": {
+      "content": "<extra_id_51>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256249": {
+      "content": "<extra_id_50>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256250": {
+      "content": "<extra_id_49>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256251": {
+      "content": "<extra_id_48>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256252": {
+      "content": "<extra_id_47>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256253": {
+      "content": "<extra_id_46>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256254": {
+      "content": "<extra_id_45>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256255": {
+      "content": "<extra_id_44>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256256": {
+      "content": "<extra_id_43>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256257": {
+      "content": "<extra_id_42>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256258": {
+      "content": "<extra_id_41>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256259": {
+      "content": "<extra_id_40>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256260": {
+      "content": "<extra_id_39>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256261": {
+      "content": "<extra_id_38>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256262": {
+      "content": "<extra_id_37>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256263": {
+      "content": "<extra_id_36>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256264": {
+      "content": "<extra_id_35>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256265": {
+      "content": "<extra_id_34>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256266": {
+      "content": "<extra_id_33>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256267": {
+      "content": "<extra_id_32>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256268": {
+      "content": "<extra_id_31>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256269": {
+      "content": "<extra_id_30>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256270": {
+      "content": "<extra_id_29>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256271": {
+      "content": "<extra_id_28>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256272": {
+      "content": "<extra_id_27>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256273": {
+      "content": "<extra_id_26>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256274": {
+      "content": "<extra_id_25>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256275": {
+      "content": "<extra_id_24>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256276": {
+      "content": "<extra_id_23>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256277": {
+      "content": "<extra_id_22>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256278": {
+      "content": "<extra_id_21>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256279": {
+      "content": "<extra_id_20>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256280": {
+      "content": "<extra_id_19>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256281": {
+      "content": "<extra_id_18>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256282": {
+      "content": "<extra_id_17>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256283": {
+      "content": "<extra_id_16>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256284": {
+      "content": "<extra_id_15>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256285": {
+      "content": "<extra_id_14>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256286": {
+      "content": "<extra_id_13>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256287": {
+      "content": "<extra_id_12>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256288": {
+      "content": "<extra_id_11>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256289": {
+      "content": "<extra_id_10>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256290": {
+      "content": "<extra_id_9>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256291": {
+      "content": "<extra_id_8>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256292": {
+      "content": "<extra_id_7>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256293": {
+      "content": "<extra_id_6>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256294": {
+      "content": "<extra_id_5>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256295": {
+      "content": "<extra_id_4>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256296": {
+      "content": "<extra_id_3>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256297": {
+      "content": "<extra_id_2>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256298": {
+      "content": "<extra_id_1>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "256299": {
+      "content": "<extra_id_0>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<extra_id_0>",
+    "<extra_id_1>",
+    "<extra_id_2>",
+    "<extra_id_3>",
+    "<extra_id_4>",
+    "<extra_id_5>",
+    "<extra_id_6>",
+    "<extra_id_7>",
+    "<extra_id_8>",
+    "<extra_id_9>",
+    "<extra_id_10>",
+    "<extra_id_11>",
+    "<extra_id_12>",
+    "<extra_id_13>",
+    "<extra_id_14>",
+    "<extra_id_15>",
+    "<extra_id_16>",
+    "<extra_id_17>",
+    "<extra_id_18>",
+    "<extra_id_19>",
+    "<extra_id_20>",
+    "<extra_id_21>",
+    "<extra_id_22>",
+    "<extra_id_23>",
+    "<extra_id_24>",
+    "<extra_id_25>",
+    "<extra_id_26>",
+    "<extra_id_27>",
+    "<extra_id_28>",
+    "<extra_id_29>",
+    "<extra_id_30>",
+    "<extra_id_31>",
+    "<extra_id_32>",
+    "<extra_id_33>",
+    "<extra_id_34>",
+    "<extra_id_35>",
+    "<extra_id_36>",
+    "<extra_id_37>",
+    "<extra_id_38>",
+    "<extra_id_39>",
+    "<extra_id_40>",
+    "<extra_id_41>",
+    "<extra_id_42>",
+    "<extra_id_43>",
+    "<extra_id_44>",
+    "<extra_id_45>",
+    "<extra_id_46>",
+    "<extra_id_47>",
+    "<extra_id_48>",
+    "<extra_id_49>",
+    "<extra_id_50>",
+    "<extra_id_51>",
+    "<extra_id_52>",
+    "<extra_id_53>",
+    "<extra_id_54>",
+    "<extra_id_55>",
+    "<extra_id_56>",
+    "<extra_id_57>",
+    "<extra_id_58>",
+    "<extra_id_59>",
+    "<extra_id_60>",
+    "<extra_id_61>",
+    "<extra_id_62>",
+    "<extra_id_63>",
+    "<extra_id_64>",
+    "<extra_id_65>",
+    "<extra_id_66>",
+    "<extra_id_67>",
+    "<extra_id_68>",
+    "<extra_id_69>",
+    "<extra_id_70>",
+    "<extra_id_71>",
+    "<extra_id_72>",
+    "<extra_id_73>",
+    "<extra_id_74>",
+    "<extra_id_75>",
+    "<extra_id_76>",
+    "<extra_id_77>",
+    "<extra_id_78>",
+    "<extra_id_79>",
+    "<extra_id_80>",
+    "<extra_id_81>",
+    "<extra_id_82>",
+    "<extra_id_83>",
+    "<extra_id_84>",
+    "<extra_id_85>",
+    "<extra_id_86>",
+    "<extra_id_87>",
+    "<extra_id_88>",
+    "<extra_id_89>",
+    "<extra_id_90>",
+    "<extra_id_91>",
+    "<extra_id_92>",
+    "<extra_id_93>",
+    "<extra_id_94>",
+    "<extra_id_95>",
+    "<extra_id_96>",
+    "<extra_id_97>",
+    "<extra_id_98>",
+    "<extra_id_99>",
+    "<extra_id_100>",
+    "<extra_id_101>",
+    "<extra_id_102>",
+    "<extra_id_103>",
+    "<extra_id_104>",
+    "<extra_id_105>",
+    "<extra_id_106>",
+    "<extra_id_107>",
+    "<extra_id_108>",
+    "<extra_id_109>",
+    "<extra_id_110>",
+    "<extra_id_111>",
+    "<extra_id_112>",
+    "<extra_id_113>",
+    "<extra_id_114>",
+    "<extra_id_115>",
+    "<extra_id_116>",
+    "<extra_id_117>",
+    "<extra_id_118>",
+    "<extra_id_119>",
+    "<extra_id_120>",
+    "<extra_id_121>",
+    "<extra_id_122>",
+    "<extra_id_123>",
+    "<extra_id_124>",
+    "<extra_id_125>",
+    "<extra_id_126>",
+    "<extra_id_127>",
+    "<extra_id_128>",
+    "<extra_id_129>",
+    "<extra_id_130>",
+    "<extra_id_131>",
+    "<extra_id_132>",
+    "<extra_id_133>",
+    "<extra_id_134>",
+    "<extra_id_135>",
+    "<extra_id_136>",
+    "<extra_id_137>",
+    "<extra_id_138>",
+    "<extra_id_139>",
+    "<extra_id_140>",
+    "<extra_id_141>",
+    "<extra_id_142>",
+    "<extra_id_143>",
+    "<extra_id_144>",
+    "<extra_id_145>",
+    "<extra_id_146>",
+    "<extra_id_147>",
+    "<extra_id_148>",
+    "<extra_id_149>",
+    "<extra_id_150>",
+    "<extra_id_151>",
+    "<extra_id_152>",
+    "<extra_id_153>",
+    "<extra_id_154>",
+    "<extra_id_155>",
+    "<extra_id_156>",
+    "<extra_id_157>",
+    "<extra_id_158>",
+    "<extra_id_159>",
+    "<extra_id_160>",
+    "<extra_id_161>",
+    "<extra_id_162>",
+    "<extra_id_163>",
+    "<extra_id_164>",
+    "<extra_id_165>",
+    "<extra_id_166>",
+    "<extra_id_167>",
+    "<extra_id_168>",
+    "<extra_id_169>",
+    "<extra_id_170>",
+    "<extra_id_171>",
+    "<extra_id_172>",
+    "<extra_id_173>",
+    "<extra_id_174>",
+    "<extra_id_175>",
+    "<extra_id_176>",
+    "<extra_id_177>",
+    "<extra_id_178>",
+    "<extra_id_179>",
+    "<extra_id_180>",
+    "<extra_id_181>",
+    "<extra_id_182>",
+    "<extra_id_183>",
+    "<extra_id_184>",
+    "<extra_id_185>",
+    "<extra_id_186>",
+    "<extra_id_187>",
+    "<extra_id_188>",
+    "<extra_id_189>",
+    "<extra_id_190>",
+    "<extra_id_191>",
+    "<extra_id_192>",
+    "<extra_id_193>",
+    "<extra_id_194>",
+    "<extra_id_195>",
+    "<extra_id_196>",
+    "<extra_id_197>",
+    "<extra_id_198>",
+    "<extra_id_199>",
+    "<extra_id_200>",
+    "<extra_id_201>",
+    "<extra_id_202>",
+    "<extra_id_203>",
+    "<extra_id_204>",
+    "<extra_id_205>",
+    "<extra_id_206>",
+    "<extra_id_207>",
+    "<extra_id_208>",
+    "<extra_id_209>",
+    "<extra_id_210>",
+    "<extra_id_211>",
+    "<extra_id_212>",
+    "<extra_id_213>",
+    "<extra_id_214>",
+    "<extra_id_215>",
+    "<extra_id_216>",
+    "<extra_id_217>",
+    "<extra_id_218>",
+    "<extra_id_219>",
+    "<extra_id_220>",
+    "<extra_id_221>",
+    "<extra_id_222>",
+    "<extra_id_223>",
+    "<extra_id_224>",
+    "<extra_id_225>",
+    "<extra_id_226>",
+    "<extra_id_227>",
+    "<extra_id_228>",
+    "<extra_id_229>",
+    "<extra_id_230>",
+    "<extra_id_231>",
+    "<extra_id_232>",
+    "<extra_id_233>",
+    "<extra_id_234>",
+    "<extra_id_235>",
+    "<extra_id_236>",
+    "<extra_id_237>",
+    "<extra_id_238>",
+    "<extra_id_239>",
+    "<extra_id_240>",
+    "<extra_id_241>",
+    "<extra_id_242>",
+    "<extra_id_243>",
+    "<extra_id_244>",
+    "<extra_id_245>",
+    "<extra_id_246>",
+    "<extra_id_247>",
+    "<extra_id_248>",
+    "<extra_id_249>",
+    "<extra_id_250>",
+    "<extra_id_251>",
+    "<extra_id_252>",
+    "<extra_id_253>",
+    "<extra_id_254>",
+    "<extra_id_255>",
+    "<extra_id_256>",
+    "<extra_id_257>",
+    "<extra_id_258>",
+    "<extra_id_259>",
+    "<extra_id_260>",
+    "<extra_id_261>",
+    "<extra_id_262>",
+    "<extra_id_263>",
+    "<extra_id_264>",
+    "<extra_id_265>",
+    "<extra_id_266>",
+    "<extra_id_267>",
+    "<extra_id_268>",
+    "<extra_id_269>",
+    "<extra_id_270>",
+    "<extra_id_271>",
+    "<extra_id_272>",
+    "<extra_id_273>",
+    "<extra_id_274>",
+    "<extra_id_275>",
+    "<extra_id_276>",
+    "<extra_id_277>",
+    "<extra_id_278>",
+    "<extra_id_279>",
+    "<extra_id_280>",
+    "<extra_id_281>",
+    "<extra_id_282>",
+    "<extra_id_283>",
+    "<extra_id_284>",
+    "<extra_id_285>",
+    "<extra_id_286>",
+    "<extra_id_287>",
+    "<extra_id_288>",
+    "<extra_id_289>",
+    "<extra_id_290>",
+    "<extra_id_291>",
+    "<extra_id_292>",
+    "<extra_id_293>",
+    "<extra_id_294>",
+    "<extra_id_295>",
+    "<extra_id_296>",
+    "<extra_id_297>",
+    "<extra_id_298>",
+    "<extra_id_299>"
+  ],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "</s>",
+  "extra_ids": 300,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "T5Tokenizer",
+  "unk_token": "<unk>"
+}

models/Wan2.1-VACE-1.3B/model_components.json

@@ -0,0 +1,8 @@
+{
+  "loader": "DiffSynth ModelConfig: one str/list per component",
+  "transformer": "transformer/diffusion_pytorch_model.safetensors.index.json",
+  "text_encoder": "text_encoder/model.safetensors.index.json",
+  "vae": "Wan2.1_VAE.pth",
+  "tokenizer": "google/umt5-xxl",
+  "tensor_key_architecture_conversion": false
+}

models/Wan2.1-VACE-1.3B/text_encoder/README.md

@@ -0,0 +1,24 @@
+---
+tags:
+- safetensors
+- lossless-resharding
+---
+# Wan native umT5-XXL BF16 text encoder (lossless PyTorch storage to safetensors)
+
+3 standard safetensors shards, each at most
+5,000,000,000 bytes **including the header**. Native tensor names,
+shapes, dtypes and raw value bytes are unchanged. No model construction,
+quantization, inference, training, GPU allocation or upload was performed.
+
+Source/base: `Wan-AI/Wan2.1-VACE-1.3B`.
+Raw tensor data: 11,361,820,672 bytes, 242 tensors.
+`model.safetensors.index.json` maps all tensor names to their shards.
+`reshard_manifest.json` records source/file hashes and independently verified
+per-tensor SHA256. For a native DiffSynth component, pass the **list of shard
+paths** to `ModelConfig(path=[...])`; this export is not an architecture/key
+conversion into a Transformers or diffusers model.
+
+PyTorch ZIP conversion, when applicable, uses restricted `weights_only=True`
+FakeTensor metadata loading and streams original complete storages without
+executing unrestricted pickle. Obtain/review the original model license before
+redistribution. This directory is losslessly prepared from local artifacts.

models/Wan2.1-VACE-1.3B/text_encoder/model.safetensors.index.json

@@ -0,0 +1,249 @@
+{
+  "metadata": {
+    "total_size": 11361820672
+  },
+  "weight_map": {
+    "token_embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.0.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.0.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.0.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.0.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.0.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.0.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.0.ffn.gate.0.weight": "model-00003-of-00003.safetensors",
+    "blocks.0.ffn.fc1.weight": "model-00003-of-00003.safetensors",
+    "blocks.0.ffn.fc2.weight": "model-00003-of-00003.safetensors",
+    "blocks.0.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.1.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.1.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.1.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.1.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.2.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.3.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.4.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.5.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.6.ffn.fc2.weight": "model-00003-of-00003.safetensors",
+    "blocks.6.pos_embedding.embedding.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.norm1.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.attn.q.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.attn.k.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.attn.v.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.attn.o.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.norm2.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.ffn.gate.0.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.ffn.fc1.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.ffn.fc2.weight": "model-00003-of-00003.safetensors",
+    "blocks.7.pos_embedding.embedding.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.norm1.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.attn.q.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.attn.k.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.attn.v.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.attn.o.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.norm2.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.ffn.gate.0.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.ffn.fc1.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.ffn.fc2.weight": "model-00003-of-00003.safetensors",
+    "blocks.8.pos_embedding.embedding.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.norm1.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.attn.q.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.attn.k.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.attn.v.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.attn.o.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.norm2.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.ffn.gate.0.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.ffn.fc1.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.ffn.fc2.weight": "model-00003-of-00003.safetensors",
+    "blocks.9.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.10.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.11.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.12.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.13.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.14.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.15.pos_embedding.embedding.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.norm1.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.attn.q.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.attn.k.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.attn.v.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.attn.o.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.norm2.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.ffn.gate.0.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.ffn.fc1.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.ffn.fc2.weight": "model-00001-of-00003.safetensors",
+    "blocks.16.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.17.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.18.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.19.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.20.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.21.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.22.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.norm1.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.attn.q.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.attn.k.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.attn.v.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.attn.o.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.norm2.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.ffn.gate.0.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.ffn.fc1.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.ffn.fc2.weight": "model-00002-of-00003.safetensors",
+    "blocks.23.pos_embedding.embedding.weight": "model-00002-of-00003.safetensors",
+    "norm.weight": "model-00002-of-00003.safetensors"
+  }
+}

models/Wan2.1-VACE-1.3B/text_encoder/reshard_manifest.json

@@ -0,0 +1,306 @@
+{
+  "spec": {
+    "source": {
+      "type": "torch_zip_state_dict",
+      "path": "/pfs/shared_models/Wan2.1-VACE-1.3B/models_t5_umt5-xxl-enc-bf16.pth",
+      "metadata_loader": "weights_only=True, mmap=True, FakeTensorMode",
+      "torch_version": "2.11.0+cu130"
+    },
+    "source_files": [
+      {
+        "name": "models_t5_umt5-xxl-enc-bf16.pth",
+        "bytes": 11361920418,
+        "mtime_ns": 1782377837411491570,
+        "header_sha256": "1c8de01450004cf34fcadb3634ea291a524aff3525a7ef305cce15a87eac4477"
+      }
+    ],
+    "max_shard_bytes": 5000000000,
+    "tensor_count": 242,
+    "raw_tensor_bytes": 11361820672,
+    "shard_count": 3,
+    "prefix": "model",
+    "kind": "Wan native umT5-XXL BF16 text encoder (lossless PyTorch storage to safetensors)",
+    "base_model": "Wan-AI/Wan2.1-VACE-1.3B"
+  },
+  "created_at_UTC": "2026-11-02T14:38:10.051757+00:00",
+  "source_file_sha256": {
+    "models_t5_umt5-xxl-enc-bf16.pth": "7cace0da2b446bbbbc57d031ab6cf163a3d59b366da94e5afe36745b746fd81d"
+  },
+  "output_shards": [
+    {
+      "name": "model-00001-of-00003.safetensors",
+      "bytes": 4935827416,
+      "sha256": "19455304c63fe471f7241a6785ef804b8012edd8ce9f30c74e8825f03413c96b",
+      "tensor_count": 79
+    },
+    {
+      "name": "model-00002-of-00003.safetensors",
+      "bytes": 4932780944,
+      "sha256": "5cbed706d3edd448e4d32188892cd87ed8a1223207d2482d09a40ca4cfbed6ab",
+      "tensor_count": 129
+    },
+    {
+      "name": "model-00003-of-00003.safetensors",
+      "bytes": 1493237128,
+      "sha256": "e56bfcc518f43f1fd83727e673cc121a171594082fc9e14164179363fbccc182",
+      "tensor_count": 34
+    }
+  ],
+  "small_files": [],
+  "tensor_sha256": {
+    "token_embedding.weight": "7a07c1fda17c2db86f92037bcedbca31f19ac2030de35b7eea37671015335392",
+    "blocks.0.norm1.weight": "eb6b648da65ef517c917be4334104438fafacb0341387db41bfaa2dcd41da7c9",
+    "blocks.0.pos_embedding.embedding.weight": "16ac858da3c2f9d3e8773bd6cab51a98aeab5fd2ef5cd60e054d4d7b5f8670e4",
+    "blocks.9.pos_embedding.embedding.weight": "14a23351d2bc454b74707e6265d24bfb5f8af652f469a912d780659e82c0f98c",
+    "blocks.10.norm1.weight": "895b83102ddf6ae128dc855a81bc7bfcbd50175844ff5f1da76155958f7d8fd5",
+    "blocks.10.attn.q.weight": "f8a9682cb265bee88b20777d757b1ee839b6952d7c6d59299891e07fa3d4210c",
+    "blocks.10.attn.k.weight": "1028f56d54e2b1bfc76be29a4f7c52eef025aed6c673bef44a71d3c3e7e99cc6",
+    "blocks.10.attn.v.weight": "f5e10bb068f365e9466716625f80949dd595491ba65ef75f733bdcd926751db0",
+    "blocks.10.attn.o.weight": "a020ebd2876019fb2e4a842ba5dee8dc7f10efa2c9aa54ad8814c1e9b6ba0a31",
+    "blocks.10.norm2.weight": "95bc6939ecec0a67f19607dcef6c3dc1fda14b27dae2032bd6859ae94c06c1ba",
+    "blocks.10.ffn.gate.0.weight": "2e608c8d619512c18c3ad2516f40b43a773e89ce1ea304b103736759d276543e",
+    "blocks.10.ffn.fc1.weight": "1aff1e3ebb6828541dd3e71adff1a0edcfb5ae7b3e539e289fef3ca3bc968cd3",
+    "blocks.10.ffn.fc2.weight": "9313b40b832c64355a645324b87d47d815614022171417147d64a8f13835092f",
+    "blocks.1.norm1.weight": "79d099d3e2205bb5189fda739a0c4bd8cfd7685550a7105faf9b3b43a70a9fa9",
+    "blocks.10.pos_embedding.embedding.weight": "5760272f0d405bf9f515c2dc16adc79544cb83aace318903abc51e3c16d551aa",
+    "blocks.11.norm1.weight": "970175d76645814106109485872f163027d13118775f4b0b78ddc5e952c0e5fc",
+    "blocks.11.attn.q.weight": "4e3b3cccc7a4f200efb122d8a905d0cf3c05f82bee53b972df0de497b1ab420f",
+    "blocks.11.attn.k.weight": "21cd5e9428308c17f2fbc18cb75be2a7b96328886d216e4a47960995dba904b9",
+    "blocks.11.attn.v.weight": "4d20ec68a33259b49a03b5f07a67cfd76c02ad8f44aed1f41d5c7e4518977894",
+    "blocks.11.attn.o.weight": "9ffb65f3d701a4575c3d54d3666bf81162129734944aa7b8b018127d3c2729e9",
+    "blocks.11.norm2.weight": "4bc4ddf94ebb4c2288348d7d9fc33b222f8016b6ab668abdc92cde5e587efe7c",
+    "blocks.11.ffn.gate.0.weight": "33108266cb1d8de5fa3da0f9d227289c02c03c2735a5cc8de5f19bdf5fed402b",
+    "blocks.11.ffn.fc1.weight": "1e61f152f47aeeabf10c17614853beded1b75ffd5d527c4d542479a399965b03",
+    "blocks.11.ffn.fc2.weight": "f402bac9ebf49449ee10eb65c06555742b473bb854da1c89b83e566eab2f883b",
+    "blocks.1.attn.q.weight": "6b125037ccbfb87619533d5e793869919afc69fb6a7004f0666b05f322bf5a8c",
+    "blocks.11.pos_embedding.embedding.weight": "9fb2d7a0cad0c4f5e44a830ae5ad0e10993d72dd6133e12904451092528c1579",
+    "blocks.12.norm1.weight": "cf0aad6324e6212cd4203eea266d174ead89cf6f431a7fc696f66b7f6be4858b",
+    "blocks.12.attn.q.weight": "2dfa2e19bd505157322a18bba9c3356478cbf171307d973595beee59159bd832",
+    "blocks.12.attn.k.weight": "ddec0e26ec89939ee78aaf565c81be021159adf54c284020e2e15a76772af7c9",
+    "blocks.12.attn.v.weight": "2c4ca7906364f66478b40edbe21c5e37fa1c5690bbc320f8e5e79b62506cf4ac",
+    "blocks.12.attn.o.weight": "59f35c21aed9c720b96cf1b61886c1caece9481497791847892bc99ec7f02e93",
+    "blocks.12.norm2.weight": "bf5d6e4673cd5408b3c92616528edb8bb1e6293205b077c2f1b57d00f52d7239",
+    "blocks.12.ffn.gate.0.weight": "112686cad680307fc9ac6d76b3f875ed96e5ceac1a0587a8b82043d9f16fef91",
+    "blocks.12.ffn.fc1.weight": "483d9c99b5637c4ec21787c9f353385b60c9dcdfaf22ec808b6bc411785e2c72",
+    "blocks.12.ffn.fc2.weight": "fde9012c28040acf3aecc2fd4e077c2c15be3966a1637474ee56c7c0102c63e8",
+    "blocks.1.attn.k.weight": "bba980395ba5472dace167e0f8c8a52de778338cba8ee448959cf7f9e46bdcec",
+    "blocks.12.pos_embedding.embedding.weight": "503142208fd4786255ccb7c3ac8888af71fa24bffb7f87ff028c07144e1b1a53",
+    "blocks.13.norm1.weight": "89533e374674aa99b09a38cd264d1971e7c5a9360aec585da61e172b49eba73a",
+    "blocks.13.attn.q.weight": "ee6e823f923b3944ab0e0e50df26fc024ace3fc29e2b604c49f5fbb8cbdfc52c",
+    "blocks.13.attn.k.weight": "4cd8fe6fbc119e25e0b44317c1ef6d003bd42f0029ee35c7c00552058a61a424",
+    "blocks.13.attn.v.weight": "bfc69eebcf6d347ed99e9d0dc68bd9f53b47ea3104b2e2e244def19d91ed0008",
+    "blocks.13.attn.o.weight": "15eec11fc66ae867044e68a0500d639689b1fd0639fb150769a89390ee6cb8bc",
+    "blocks.13.norm2.weight": "725e9d5bbda12b83d6dad4d990c65fa401c83521dcc1f622351ac08e16717517",
+    "blocks.13.ffn.gate.0.weight": "a5251eaf3c1219c3280abd0b7c82184dc9b06197b4a1b104785dc57d69cd09a1",
+    "blocks.13.ffn.fc1.weight": "273d13056440d9ee4f12a2459c9443c6f43f08c0406474ffb8a80fe3473624fa",
+    "blocks.13.ffn.fc2.weight": "152640d33d6e7eca7323f13e36a25ee6448418ae3df41e263ca692a8e28e05d3",
+    "blocks.1.attn.v.weight": "84e899d8a8274e35c434e0200fc1b4d81b137f1c042c423290059a4fd1eee25a",
+    "blocks.13.pos_embedding.embedding.weight": "be0ec2f3aca7f6b4cbb5c8e66ac0287508de13d2f2117a2d5feb05373de7ea71",
+    "blocks.14.norm1.weight": "b79255a2acfd2ab928804e7a255662a9b56ace8ad585b3ce20c19c814f619c35",
+    "blocks.14.attn.q.weight": "db0892fa78c968cf912cf3d49a46bee45eb7a9ee37e491bfad947134bcb37a9e",
+    "blocks.14.attn.k.weight": "e970280372095426c7aa393046878f760bc3b62edf393ed8883c3331a10fe1b2",
+    "blocks.14.attn.v.weight": "09da368e33ef58b3483eb533427bc24ab1bb012f8df2dc35de5dd1973308f279",
+    "blocks.14.attn.o.weight": "42de186d4acae0a96f6dab1ae7c5cbb1bc8db9a3fcb49c0be6d0eb7441e9b2c3",
+    "blocks.14.norm2.weight": "ab1e3e39dffab58a7ea8143202b5dccac8790cad065ff8e72f2ae517e63ff9c1",
+    "blocks.14.ffn.gate.0.weight": "2b661ddfe3bd0c2db5bd9481f81f86d518dc726869d16859fbd4965cc930f41d",
+    "blocks.14.ffn.fc1.weight": "6626f605bcc9837deb063c4676b2a839c95e6f2ab5c91d5ac3493f2fa837460d",
+    "blocks.14.ffn.fc2.weight": "a09ee2ec173fd9591349c5651633f0cc62f32158280d6bdd6a35cf12b0448042",
+    "blocks.1.attn.o.weight": "b3bf3b4f8ea2983095b36e9b399c9a5f691b16c2c307608bbfb04360b79763a1",
+    "blocks.14.pos_embedding.embedding.weight": "b1d951840608f03369c14d8e9fbe05d8fce8fb07663711409dae83c09f3af9dd",
+    "blocks.15.norm1.weight": "3ce9cb270a024cbf1d8924afd8f9a6580ac1e040d8c63e2e2fb324b843dbf7e7",
+    "blocks.15.attn.q.weight": "d1cce37aea0f7ac629cb341e76ea04e5e821a2cba1c586e3a543bb6e20e0b407",
+    "blocks.15.attn.k.weight": "5973e90b71324443eec6d80b363af37c8b675292fe2b621c3105a2641685aeec",
+    "blocks.15.attn.v.weight": "25d6691751e0a48f5058f34253fffd70108ab46a795352ff5c4c0a919c904ba8",
+    "blocks.15.attn.o.weight": "e6e7f81035f2536f3378e84473d60b34fa8e5c76ecc8ec9c7d030deb8c1fbc91",
+    "blocks.15.norm2.weight": "994ed82cf04b70ef7bc776af9a36cc4ba0b97e61740d0865d72a5e1bec489af5",
+    "blocks.15.ffn.gate.0.weight": "37056e4496018e93ac8d16381e90cce9082d85beec6178b5edb934d71d3e2e6a",
+    "blocks.15.ffn.fc1.weight": "776ecde1f18fa137c5825b0d01685962f5ec6e14c0ecce5598f7f45d1860e202",
+    "blocks.15.ffn.fc2.weight": "6ffe87ee115a9cb6026e771967ddbb0591de0df35d52dca61566697fb9489007",
+    "blocks.1.norm2.weight": "f996accd3798546632edaf15f09cd96ced753ec92b3882d258a812c27ae96aba",
+    "blocks.15.pos_embedding.embedding.weight": "dfe43901e16ab222fee5c2e4d4592c9db61c692681284c5e0d33075acc35e469",
+    "blocks.16.norm1.weight": "8d8b4bda7490bfd0f2d0873e2a2b4f5d7fc8cc32a8af5304b71cb18502c98f3e",
+    "blocks.16.attn.q.weight": "0b83e016035278c40769737bb6497bb010d40cdc33ad901b6f0ed7502a80b060",
+    "blocks.16.attn.k.weight": "aefcd9be2658d14ca27911725a9e1f83a790cc9540bad2ab78bb94a742083c0a",
+    "blocks.16.attn.v.weight": "bca4aae294c9f2306fb0c95d576cef2767a1532856b488667419ffe4c2adf26b",
+    "blocks.16.attn.o.weight": "6599700127a6f7bc90e970d8d27d60d351f50e60da1512e03330a5c3ac8437c6",
+    "blocks.16.norm2.weight": "7fdc244aa9461af8b6a0cac88bbc2bf276c4225b8242448c43f5379857fe9d33",
+    "blocks.16.ffn.gate.0.weight": "e836842d9ca9c6c84353b35846403b5f6f14ff4009b8aded4369c36f24b1e4de",
+    "blocks.16.ffn.fc1.weight": "c23f9e0d634f83a0e8d88d93f2ff744a3ce6b89857771b4d4d925def43c72f29",
+    "blocks.16.ffn.fc2.weight": "ff74fe9dba5dc746573c4c65e780f51d1bef6b347c53bd9ff97bfc6b3a1f137a",
+    "blocks.1.ffn.gate.0.weight": "5663a56b7e66085f2b5e3305be90b8a42f261e7533e0b7901979223c6fdf1869",
+    "blocks.16.pos_embedding.embedding.weight": "2837a8a4abc3b719e19db9f2829ba293bc73719c1443da46d2df61612efd7258",
+    "blocks.17.norm1.weight": "d68d2c485e4d685a61369662aa9f4ae462d3af32825991eedbf9ffaf7cb0e4f8",
+    "blocks.17.attn.q.weight": "5de112b2aa6484081b946f5755e07bebf11accf7b6616ac0ffa2efec8c2e9adc",
+    "blocks.17.attn.k.weight": "89b736a76bbda9ddcfdc03166daa5056d435773a2f679dc72e6ceab486c9b5d9",
+    "blocks.17.attn.v.weight": "0574d4274270e960af4c7aefa38e3a99007fee513e0d8f9823e9c5e4da56d936",
+    "blocks.17.attn.o.weight": "8c41d63abd73e0f6e064f689328b0167e548928cbcb334bbf0d9e80015831fde",
+    "blocks.17.norm2.weight": "4d149ada746cab606b657ec1b33a2113816309c3fdc2add16fa0eafe2a0f9b3f",
+    "blocks.17.ffn.gate.0.weight": "e1f57a1282ceb2be858997ce5c2837823435011afeedcaf9878dd58aa9acac79",
+    "blocks.17.ffn.fc1.weight": "2d2b01def57a571b2c7427f0de2b70e6489d92740ecd720addc99c68328e0f62",
+    "blocks.17.ffn.fc2.weight": "3afa39c2c8bfc29a514d7c891299f0579acac4dfda925607b476a336924a5c41",
+    "blocks.1.ffn.fc1.weight": "e76ded41f39e97b111d827c72d5a5a5345f7f4f6c1ee4ef7689363729fd5c04d",
+    "blocks.17.pos_embedding.embedding.weight": "bdd06f96c5e09993a166576039a6d9e38ec694df35220a73f3f1ea41cc0a6081",
+    "blocks.18.norm1.weight": "dd8d76ae6f1b22822c4d37c6b73b1c3318089a2fe4d822785c9ed773d7abf7e6",
+    "blocks.18.attn.q.weight": "ada1c49f07cfdcb1dbd79a3c157744c6a939fc410145711a81a7198c3bbef2c4",
+    "blocks.18.attn.k.weight": "bc99b514900264a1fe07eab83774448efae6df86db00c7089ed02e234eac3da7",
+    "blocks.18.attn.v.weight": "729700ebaebb1d9e22861ba1cbc3bab0b92fc84585595c71e5eae3613d931179",
+    "blocks.18.attn.o.weight": "b50c55e3a5e2ca854863c3004246c08b09d011989f30f84aa22094d448209b4e",
+    "blocks.18.norm2.weight": "6db348791a981ca0f08903b7410bce9b7a3e087da19175b50cef9ee08832fd49",
+    "blocks.18.ffn.gate.0.weight": "35d1107cc75a03f6f8c69b42d52f6cccbca9122253e898d960c07fffd129ce2e",
+    "blocks.18.ffn.fc1.weight": "0981fe226990adda68aa0d2e5df3142863042fec69d2af3c5b705622ee7cdebc",
+    "blocks.18.ffn.fc2.weight": "3d6a62240e6ce9b0ed22792470bd9980e554f504cbc1b78bdfe6df5197ab900f",
+    "blocks.1.ffn.fc2.weight": "5e8eeb33950b0a10b5bbaf5d38d262a4684678feeedc50ac0af480e88768c99f",
+    "blocks.18.pos_embedding.embedding.weight": "d2fd4afdb40cb190503301e39a12ca67106ff0cf72e221c78cf5a490549b2b35",
+    "blocks.19.norm1.weight": "2e40788b80e9e719367348985a1125c1f5b5ebea85296d9e28d6ea2d060c3711",
+    "blocks.19.attn.q.weight": "4175ab7f7998829fce6104309447ec5229dbcee4821a05edb17ddf5afd22dd37",
+    "blocks.19.attn.k.weight": "06673b88a4f5576fbfc6d961d7e89c0fc43956e45ef47b6cd851f5be3590a6d8",
+    "blocks.19.attn.v.weight": "6d438ffdd1a48c87ae61cc3c6a57a768883c625019447b7f0c6d1e80777e7c0a",
+    "blocks.19.attn.o.weight": "2e3eb1c3cb5de086202688db3065bc27af0483afaa1064fb568ff06408618441",
+    "blocks.19.norm2.weight": "e28c5a32a6e1110948f7e1ed11714df8a189b3477ca8f6bee7bde9598082e968",
+    "blocks.19.ffn.gate.0.weight": "8e6a793fbf4da17b6a67e19053dc1eee38856949cfe3448b38e63de97df667ee",
+    "blocks.19.ffn.fc1.weight": "cec80566c4d66b2e093570ba2ee3d4e7e577cad2514fe201a26307619718f67b",
+    "blocks.19.ffn.fc2.weight": "7889e9dac34607dd19dbbfd74893941124beb5794a473f399d39531e44c32bf4",
+    "blocks.0.attn.q.weight": "d21b1aedd645f18ba0986ac2d2daf518bd65021201d41283a30759d138d6771f",
+    "blocks.1.pos_embedding.embedding.weight": "37e18f4a1bda134ec51909d4d05089176e2cc0472a9686bc5e20e35f59efbe8c",
+    "blocks.19.pos_embedding.embedding.weight": "3257572f4a78cff35df8f4b617435c31a1c4492a6a590a62bd7a07fb16fbdb47",
+    "blocks.20.norm1.weight": "72dc264da9dc2818e424726ddb14745a8d13664b1e4f65c0cb214e1dca67141e",
+    "blocks.20.attn.q.weight": "d1d91d4eeb4ab2991a39dab2397777882814a11d818a17b94574c15bc85ce6e4",
+    "blocks.20.attn.k.weight": "ebc45606b255dd92e8f015344176008484564df95bb5758c0275db271107655c",
+    "blocks.20.attn.v.weight": "37db03e3aed18a10be07e20237a3d92aebddd9be6ac2371d71ba5a1a4715b8c9",
+    "blocks.20.attn.o.weight": "0d99252e4551981c1ac68cb7d45657c41a5230367081c03b2339921dc1e0210c",
+    "blocks.20.norm2.weight": "6ef4f7543835e6f8824d1cec8537f7a3488d617385e31396404910a2b0136e1d",
+    "blocks.20.ffn.gate.0.weight": "6f63405e91b69aeb063b67cf071592f7177628cb786554c920e584e66bd50a94",
+    "blocks.20.ffn.fc1.weight": "2b8038c5ab90f06dd9c7c53266c003f144c39ced94122c1897f956016a05c70b",
+    "blocks.20.ffn.fc2.weight": "c5e06234f261ced1cdafd5d62b6ef2ac752492999c9fde229e74489b36f5e3ad",
+    "blocks.2.norm1.weight": "6c5b209b752b82ec17e93a188359a2d113180d7c5ccc9381233a9693efc862bc",
+    "blocks.20.pos_embedding.embedding.weight": "d6b9c3135bfaa11dc0acd6a23f06319be7bb247b8070fc1cfe70a928f8a8df81",
+    "blocks.21.norm1.weight": "643b6600f4b82436899f39b3111d0cf26acf3c7347b9d8468fd45c3099b5a37d",
+    "blocks.21.attn.q.weight": "addc9f461416416c69807af4cd1616cbc692ac7e6a872a580b852661b94e70fe",
+    "blocks.21.attn.k.weight": "fd1c67e724995a1411d369bb1a453754ca2de2352a211f823e917537ffafdc5d",
+    "blocks.21.attn.v.weight": "512130bf64f84225b89ec703375b556f53639119a5f7d0b88d1aaea96a67fa10",
+    "blocks.21.attn.o.weight": "f30e987abfe948971134a03f726589cbb3b6d6865d4ab927fb37060f739d31a4",
+    "blocks.21.norm2.weight": "cd2b8874f2f2123389231563849f8a390707aeacee94417782bc36c264da5428",
+    "blocks.21.ffn.gate.0.weight": "a2314c04fb1ed25f395f59a768b467388d905086987026c0a073cf4f8a3e2d9d",
+    "blocks.21.ffn.fc1.weight": "acde23d49c23149236f48504b941e0122ba63965eb6a4bb188d4b5051c16aafb",
+    "blocks.21.ffn.fc2.weight": "2dd08d20dc169ed0d5489a37265753d402032a9f800f5f00f1ef4dbb3c5091c7",
+    "blocks.2.attn.q.weight": "3fd1aaf09538d728a6c14dda63bdbfa2cb651bb33c74da38924852eb31d19d5d",
+    "blocks.21.pos_embedding.embedding.weight": "7f3e017e3c7900b8772c8e35d05278ba09e9e15be1d000d618dee30681782dfe",
+    "blocks.22.norm1.weight": "22d6bb349f0f59ac73633b1b84b910af16b53260aa9b2f1b4f6589455d479bb1",
+    "blocks.22.attn.q.weight": "5af57f70c171e949ab14a15bd1f6ab61814e71de5612723632f70f7c34d18eb6",
+    "blocks.22.attn.k.weight": "649a2ad379b8f3bc749c9a8e87367207ece686dbb2ca4e5cde9aeab13ff5e64c",
+    "blocks.22.attn.v.weight": "e01809b1e138c72ca2e5e8209c1e38f7feb697950a3a93a5a7a1c6438c75a1d8",
+    "blocks.22.attn.o.weight": "b0a2a4ab34ffb49bd00805d2c696f56e602824ad345a30e1ee2f7006d28746c1",
+    "blocks.22.norm2.weight": "c753ae4c00b45f4255debf54d3959969655bf211e723da07eeb6c6e6b47d236f",
+    "blocks.22.ffn.gate.0.weight": "73512601eeb9bcc96f0c61b1ce758508b82ab938522dd1ffa86fe9635509988c",
+    "blocks.22.ffn.fc1.weight": "dfb8325f40f5c1add432c9d7b6f58a75b335711525b791b3ad6bf9649d75596f",
+    "blocks.22.ffn.fc2.weight": "8e7a5c10f6faf197e1b48677095c99fc73e1b670e8cb650f8bfbd9e3b1c01082",
+    "blocks.2.attn.k.weight": "2c424d58ec5917de237914de18b96703ee9d6434c2d8489f077ef3552ffc623d",
+    "blocks.22.pos_embedding.embedding.weight": "7ace7ad8b48b7cfdb7c8bf7df5833cab3336984e27d0758a5e0cf760b339f7d6",
+    "blocks.23.norm1.weight": "e3087a315a53fa65fb9280ae1f63281af5ca91c3a91f0826f5d7a80515897da4",
+    "blocks.23.attn.q.weight": "be0edaf4c14122ceebfe28fe4b1c01f3ca23385ffcbaa860ad47e2f22adad712",
+    "blocks.23.attn.k.weight": "8c0c174b87efbcf51585e77087fdeaad0d72e698e2758873c2ab4260b3b7f560",
+    "blocks.23.attn.v.weight": "f1b9e11f21fc1735b864d7d2db5e223f1b3346cc36f7f4dbf6d2e3e2b6d1f391",
+    "blocks.23.attn.o.weight": "096c1fcf24e130040a68ef2fad03910871d007b1c3caaa3e83e354666702acef",
+    "blocks.23.norm2.weight": "3f4068097ce4edc953017865abef17866c9316a1c8b58d4315972f025e7a16f6",
+    "blocks.23.ffn.gate.0.weight": "ba03cefdf71949a33e84568cd28aa7650502792ccd702e91fbe8dc6d75682184",
+    "blocks.23.ffn.fc1.weight": "6353ab72c4a3e2d2900f50e3623a9e996db90355c3c245c4259e363fb062fd55",
+    "blocks.23.ffn.fc2.weight": "f8003679a687d385766e613a9aeaaf0888399b4b6dd7e58fb3fe8f3f93978292",
+    "blocks.2.attn.v.weight": "752e0fdac3af94cbbf98a004e927164e693d1ff18d205c18d36218d3c7afd168",
+    "blocks.23.pos_embedding.embedding.weight": "3f59c46e528b03853fc49d4214656878d427d9985bb88a9bac7a8c6339a896dd",
+    "norm.weight": "2ca6139fd533f095bf7fc876250201c34ae33497a5533b6e7220373a670361f5",
+    "blocks.2.attn.o.weight": "2687bb6fed941b67429b6f2ebdcab75580a0df8b7cce3f987bafc47df0cf5048",
+    "blocks.2.norm2.weight": "d6d663a8f3495520eb1f5dadb72a84225c59c658eaf4b337891dbf0614281881",
+    "blocks.2.ffn.gate.0.weight": "c2922f8b808849d2a4ab0cdef4d44a18e4d0c12b25e56dc6eac335c7426d6f2f",
+    "blocks.2.ffn.fc1.weight": "79fc1c8f66b5d079e00f355770c34bfe37020798a5e36ac8db2e1087208be344",
+    "blocks.2.ffn.fc2.weight": "c8498ac1f86f4a46cd4b7c74e123d31aa89edd0ed3261596d6d993f0f7fe3738",
+    "blocks.0.attn.k.weight": "d39907e9959057976d29050845395f794b186072bc8e371ce190594602d1a2b7",
+    "blocks.2.pos_embedding.embedding.weight": "3219422d54820a0570879ea7e006751dc0b967f82c6900ad8932884d62887987",
+    "blocks.3.norm1.weight": "364e341cee34e54159fd4dc74d102dd9a39f6ecdac34d6c50fbef3a1d2e6d1dc",
+    "blocks.3.attn.q.weight": "8fcff89bf9be9a52a8141b85676aaa40698128997bf06435de7f7dcdc6ae98e1",
+    "blocks.3.attn.k.weight": "1888300183362dbf9f917f92fe1df0c82fa79007933710bfa92c4d3aaca71210",
+    "blocks.3.attn.v.weight": "fe605c3ac3fc79d3e895c534366db0088b2ac5a54f18e6702a6ccbdd5d4c777c",
+    "blocks.3.attn.o.weight": "a887e1e11832b6969f9fff283359a8fb8c75849df373e3d5468c61b10591b0f7",
+    "blocks.3.norm2.weight": "0604138c2e4271f6ea6c2981939fb1a7393fe67f45a85d427de63fe178a8fd4e",
+    "blocks.3.ffn.gate.0.weight": "2d7a32b3fae6e3dbbb6a074256d1f1eb820a6b34c991551bd922bf42e890debc",
+    "blocks.3.ffn.fc1.weight": "7e438eaccb82c050e5fe64c10ba51f5d4061905fa7df80f1295b8fbe228a2b7e",
+    "blocks.3.ffn.fc2.weight": "969adf9812b17e60aebcc49bfc3d3c235de1b2a0608431ade4abd2222be412f2",
+    "blocks.0.attn.v.weight": "b0352b1032c1e33ea642d634e91e556b2f6082fbcc2746944251af55c7e58687",
+    "blocks.3.pos_embedding.embedding.weight": "248cda24dfe16e555969c2f6bf4f5c389f3ce0b4c5db54702ca898ca1ea5f60b",
+    "blocks.4.norm1.weight": "6024e784b6931517c957b33b35e7c078ad2130976395311a31e3b6b10c6097b7",
+    "blocks.4.attn.q.weight": "f77288b2b407db727796de345d4436a35554184286d39f5b45f18ebb70ef0835",
+    "blocks.4.attn.k.weight": "5f44375c04eda6064193b05884789a8efe96ec6fd8676626b9937bc7b6e38de4",
+    "blocks.4.attn.v.weight": "df4684c53b6f3360bee9eabc5d5c30717513af563643369038afe88a670329aa",
+    "blocks.4.attn.o.weight": "fda7a141aba6b3724c4e5bdbc4ce606a17db7bf748fac1e607f9a0dcfbbf6918",
+    "blocks.4.norm2.weight": "ee879642a4d0f10b71f5f98a508e6f8260bc2bea4de245d531c02813bc9b1312",
+    "blocks.4.ffn.gate.0.weight": "b8ba12171bc0022d297798f036efcc2d11c9849c114bb00b964f1c7cecf6f880",
+    "blocks.4.ffn.fc1.weight": "52033bc97c7ff19487dfb15fef9b769f031f29a852630e1ff6d70f960712c7a6",
+    "blocks.4.ffn.fc2.weight": "cec3f614798fc63a93c67e21100a078e514a73b1091666e5e09aed6024961161",
+    "blocks.0.attn.o.weight": "7872348cae59c57676dea3a260128a161b6f4a612cf978587a1bf54d63481c3f",
+    "blocks.4.pos_embedding.embedding.weight": "6c505beaf2fee494e86510d764dbb7a5da3044386d5c827edc4890fd5cbdf877",
+    "blocks.5.norm1.weight": "dc573afb676678ff989fb605da92c3231bd47e6d4861b458b9536db4d34c1fb9",
+    "blocks.5.attn.q.weight": "dd22da2da552f4b20e938b0937febc1df0607467c696d273ec0f5c00fe55cb5f",
+    "blocks.5.attn.k.weight": "f6b1b0ffdcb4a495fec65140fdbdb5e41b8a50faea9aaa0c0607ea2f23aad580",
+    "blocks.5.attn.v.weight": "358c5f0140a7944f8c7bff6b43be57ff7e39cbfdbf886acefbc47cfc1cb58aee",
+    "blocks.5.attn.o.weight": "169543af19807eef6adef3b124a43a308a41095f160fa6c915140656b2c365d9",
+    "blocks.5.norm2.weight": "6a35204fe66780ce0501621e603bcd82110cef0566458bd86aa898da30f59e4f",
+    "blocks.5.ffn.gate.0.weight": "0515e1714b132cd1d0e4d5cfa02a8af3a71dbb6be7fa13d3ebc1f7fbf035796a",
+    "blocks.5.ffn.fc1.weight": "53c741aa4d270d8cc787952f28b1d7c8674d3e1ecaf8d4fb31b2b8d805edc112",
+    "blocks.5.ffn.fc2.weight": "b07991d0d6a9f4ba3f9bec2afae9eba4b6fff06e7aee5374e439fc58123336df",
+    "blocks.0.norm2.weight": "f2d7e2feda24b5e6c813084fa105fca6f9b8f0b445ac3810a47f52f0d2446125",
+    "blocks.5.pos_embedding.embedding.weight": "946cfcf492a5c88f55cc29dfef73c4f6e1e42dd22a1c0de708f976d5e441a98f",
+    "blocks.6.norm1.weight": "ed716972d9ad9ab1dc588863ff325aa555dd9f21633b3cd81d2e3fca524f8c74",
+    "blocks.6.attn.q.weight": "649ffa907b30ee554fc9468ae7219ab5aa9cd7a77bddaaacda894551d83dcf47",
+    "blocks.6.attn.k.weight": "c4bfdbb8e2c224242fb3b42fb292e54faec1dcb08c51262c262f8072951197a7",
+    "blocks.6.attn.v.weight": "24afa38423f157af3a78156f8e4480c6994e478fd93b45e044fcdc5ec3eb421c",
+    "blocks.6.attn.o.weight": "5f2da167ff70b582fc154baa75aca00157d61bb061d9d49a306e047be51b5c38",
+    "blocks.6.norm2.weight": "5d589fedf6581d068539ec323650c8240b410d9ad7eb6e799c86e631995e0ea6",
+    "blocks.6.ffn.gate.0.weight": "b1715bc1a5a21e8a1a4304da70512f0bc34a170d77d7e1efe68b00c4373416eb",
+    "blocks.6.ffn.fc1.weight": "8cf0041e3adedde06d67fba3149ed48f7c1d58286272d2e3ba9adaa032b6dc04",
+    "blocks.6.ffn.fc2.weight": "89dd1b1817fc3b0b7cf389b4847a1be3a59cbeb406630df8a7da6f04ea73f81b",
+    "blocks.0.ffn.gate.0.weight": "055dc93056014efeef9505f02749c9919dda154065f48e9dfb3b5bf388fd8fc2",
+    "blocks.6.pos_embedding.embedding.weight": "85ef8b8dde1e8b5e22f981af2013ddc2b9a05008e063e3d5aaccb388d23adc28",
+    "blocks.7.norm1.weight": "55d0d527a8f37586b0da6b369181ab5d50e638c84a95cceffec056e9a773388f",
+    "blocks.7.attn.q.weight": "f9ea192e784a8d6eae3d3cd67b03cf486dc4a6d17c11321a59cb331beb60b84a",
+    "blocks.7.attn.k.weight": "354979905f65a164a882464852078b4d6f07d9e01c7823e9dabf918e7741956b",
+    "blocks.7.attn.v.weight": "a9418577eddd6ad5e27d4b8b9cd1a4efa1dfbb8ad2082e17fcec48059b6fea34",
+    "blocks.7.attn.o.weight": "717a19dfcaa7659c7e57939733dfa733e5075d518f2e0d493230e6e15c072e86",
+    "blocks.7.norm2.weight": "467861f3984054299d10c36289c6f1d53573bd0c0fd1d862fa5cd7abee7a92a6",
+    "blocks.7.ffn.gate.0.weight": "1792b8e5667294d6d14fd74f2130ce67526fdb307d592ee6149bcff253770bef",
+    "blocks.7.ffn.fc1.weight": "de885d63fd3a56b723abd9e4dc1ef0d58e16fd37ba134689de98e69dc1de76a7",
+    "blocks.7.ffn.fc2.weight": "5229a9087d7c8955f2bfb72860bac6e78aefbdd1e1fb76520c2116d0440f8f08",
+    "blocks.0.ffn.fc1.weight": "334367de1a1817877718fcfb56284fb3b747b18aaeeb406c1571b8135e6d3878",
+    "blocks.7.pos_embedding.embedding.weight": "e0ef496ceaefa1e7ce797349771bdd535cc689f06b5f10dca87a5c69416ba7c1",
+    "blocks.8.norm1.weight": "c46ee124175fc11b5827433f3948c7ce4b2a58e219fc958dcfbd6446fba7903a",
+    "blocks.8.attn.q.weight": "db4b7dfd987c2f4c82e0b102c5fb095b778f9df65f6bd8df726de8670dacb735",
+    "blocks.8.attn.k.weight": "8e7118586292f5a6a947e484a64d7629365087188be78fa068d2b953d44b4ad2",
+    "blocks.8.attn.v.weight": "0ebb08161096cbb156a238fc8ac6f4eedd6646a2192bedb2bb9c7d1f5f601d3a",
+    "blocks.8.attn.o.weight": "4335a2fa8fc7215993e4d344d26276515d75b22bba39bf154ba84c22128cf649",
+    "blocks.8.norm2.weight": "04295b427fa281bdef22672e30e2c5524a4ef9ac0172848d5ebdd7abc8f14a32",
+    "blocks.8.ffn.gate.0.weight": "aa04d3f9631a2e1d244a3aa0bf670632d02fbfa4ca9f1f440a3c5fd27d2acd7f",
+    "blocks.8.ffn.fc1.weight": "02c3f7c99d3613a97a186fde97d4666ef49ba007a9d033352ad455e5850937e8",
+    "blocks.8.ffn.fc2.weight": "1f7b38bc6ab72afa0aed927249916104bd3aca57c3f2558149a995a4b19fd83f",
+    "blocks.0.ffn.fc2.weight": "f445c5e99f7f41fb7c5a71d3d9e429f34a5e4c96f9cfa409ff71d688b22f0492",
+    "blocks.8.pos_embedding.embedding.weight": "216ab5eb195b5aa8b0a9355a8879878e1eebede5b818bacf3966b860e41b76f8",
+    "blocks.9.norm1.weight": "511f91c22333a8363a653903922445b707b13c9653828c06c80b14ba130a84fa",
+    "blocks.9.attn.q.weight": "1ed924db52e76904346aaf84b5f24b6c3aa880dba386ae063806ae92f50a92e5",
+    "blocks.9.attn.k.weight": "237a326aec5e287a5f200887365d879d7390ca1dd1e06a8e4bc914ceefdb3008",
+    "blocks.9.attn.v.weight": "b144ccd48692b03d4c4e69edd5a9b80955b488fbdcf5e6fe3a643ef9472ed93e",
+    "blocks.9.attn.o.weight": "fd1298bf829009c192917f2bcbcd20f9647e8692379298219c8a3ca705731151",
+    "blocks.9.norm2.weight": "ca1649a695f64c542622a6c6e4d2af64827d19bcaecd25dd6ddc0d6ea92d011f",
+    "blocks.9.ffn.gate.0.weight": "6b315d5089aae0abca0b17c4f17ea1709be04da91922a2d8cca542aa6dbcebc8",
+    "blocks.9.ffn.fc1.weight": "e536498c8102de20f4f0d359a1cc675bb0b8a451b6e81684b5c04ac5d7d84787",
+    "blocks.9.ffn.fc2.weight": "8f749319a434e3e8df116aaf289350d609af76d2d264c80c21f21be3b599daaa"
+  },
+  "output_index_sha256": "8322567493a4f08dce5d97f8621a2896a5ed1b72e0865371e3339599e077ebb2",
+  "validation": {
+    "all_tensor_names_shapes_dtypes_equal": true,
+    "all_tensor_bytes_SHA256_equal": true,
+    "all_output_shards_read_back": true,
+    "source_files_unchanged": true,
+    "max_file_limit_respected": true
+  },
+  "GPU_used": false,
+  "model_loaded": false,
+  "training_run": false,
+  "upload_run": false
+}

models/Wan2.1-VACE-1.3B/transformer/README.md

@@ -0,0 +1,24 @@
+---
+tags:
+- safetensors
+- lossless-resharding
+---
+# Wan2.1-VACE-1.3B native base transformer (DiT and VACE, not trained Any2Ego branches)
+
+2 standard safetensors shards, each at most
+5,000,000,000 bytes **including the header**. Native tensor names,
+shapes, dtypes and raw value bytes are unchanged. No model construction,
+quantization, inference, training, GPU allocation or upload was performed.
+
+Source/base: `Wan-AI/Wan2.1-VACE-1.3B`.
+Raw tensor data: 7,145,937,664 bytes, 1,264 tensors.
+`diffusion_pytorch_model.safetensors.index.json` maps all tensor names to their shards.
+`reshard_manifest.json` records source/file hashes and independently verified
+per-tensor SHA256. For a native DiffSynth component, pass the **list of shard
+paths** to `ModelConfig(path=[...])`; this export is not an architecture/key
+conversion into a Transformers or diffusers model.
+
+PyTorch ZIP conversion, when applicable, uses restricted `weights_only=True`
+FakeTensor metadata loading and streams original complete storages without
+executing unrestricted pickle. Obtain/review the original model license before
+redistribution. This directory is losslessly prepared from local artifacts.

native_reader_validation.json

@@ -0,0 +1,110 @@
+{
+  "reader": "safetensors.safe_open(framework=pt, device=cpu), slices only",
+  "safetensors_files": 20,
+  "tensor_entries": 6816,
+  "files": [
+    {
+      "path": "checkpoints/caption_grpo/adapter_model.safetensors",
+      "tensor_count": 504,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "checkpoints/generator_global/ckpt.safetensors",
+      "tensor_count": 240,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "checkpoints/generator_hoi/ckpt.safetensors",
+      "tensor_count": 300,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "checkpoints/generator_spatial/ckpt.safetensors",
+      "tensor_count": 300,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "checkpoints/reward_preview/ckpt.safetensors",
+      "tensor_count": 240,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "checkpoints/sft_only/adapter_model.safetensors",
+      "tensor_count": 504,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/CLIP-ViT-H-14-laion2B-s32B-b79K/model.safetensors",
+      "tensor_count": 912,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00001-of-00004.safetensors",
+      "tensor_count": 109,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00002-of-00004.safetensors",
+      "tensor_count": 142,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00003-of-00004.safetensors",
+      "tensor_count": 137,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Qwen3-VL-8B-Instruct/model-00004-of-00004.safetensors",
+      "tensor_count": 362,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model-00001-of-00003.safetensors",
+      "tensor_count": 79,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model-00002-of-00003.safetensors",
+      "tensor_count": 129,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/text_encoder/model-00003-of-00003.safetensors",
+      "tensor_count": 34,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model-00001-of-00002.safetensors",
+      "tensor_count": 726,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "models/Wan2.1-VACE-1.3B/transformer/diffusion_pytorch_model-00002-of-00002.safetensors",
+      "tensor_count": 538,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "research/caption_dpo/epoch-2.safetensors",
+      "tensor_count": 240,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "research/joint_branch/epoch-3.safetensors",
+      "tensor_count": 480,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "research/native_narr_dit/epoch-4.safetensors",
+      "tensor_count": 600,
+      "names_shapes_dtypes_verified": true
+    },
+    {
+      "path": "research/vlm_comparison/epoch-0.safetensors",
+      "tensor_count": 240,
+      "names_shapes_dtypes_verified": true
+    }
+  ],
+  "CUDA_initialized": false,
+  "model_loaded": false,
+  "inference_run": false
+}

tools/attach_model_bundle.py

@@ -0,0 +1,109 @@
+#!/usr/bin/env python3
+"""Attach a downloaded ego-exo model bundle to code/core. Dry-run by default.
+
+Creates links only where destinations are absent. Loader patches are applied
+only to the exact known pre-sharding code version (or treated as already applied
+if hashes match); other local edits are never overwritten. No inference/upload.
+"""
+import argparse
+import hashlib
+import json
+from pathlib import Path
+import tempfile
+
+
+def digest(path):
+    return hashlib.sha256(Path(path).read_bytes()).hexdigest()
+
+
+def safe_relative(name):
+    path = Path(name)
+    if path.is_absolute() or not path.parts or '..' in path.parts or '.' in path.parts:
+        raise ValueError('unsafe relative path in loader patch')
+    return path
+
+
+def plan_install(bundle, code_root, patch_loaders=True):
+    bundle, code_root = Path(bundle).resolve(), Path(code_root).resolve()
+    if not (code_root / 'project_paths.py').is_file():
+        raise ValueError('--code-root must be the existing code/core directory')
+    if not (bundle / 'bundle_manifest.json').is_file():
+        raise ValueError('bundle is incomplete or has no verified bundle_manifest.json')
+    if json.loads((bundle / 'bundle_manifest.json').read_text()).get('status') != 'complete':
+        raise ValueError('bundle is not complete')
+    operations = []
+    for group in ('models', 'checkpoints'):
+        source_root = bundle / group
+        if not source_root.is_dir():
+            raise ValueError('missing bundle resource group: ' + group)
+        target_root = code_root / group
+        if target_root.exists() and not target_root.is_dir():
+            raise ValueError('resource parent is not a directory: ' + str(target_root))
+        for source in sorted(source_root.iterdir()):
+            if not source.is_dir():
+                continue
+            target = target_root / source.name
+            if target.is_symlink() and target.resolve() == source.resolve():
+                continue
+            if target.exists() or target.is_symlink():
+                raise ValueError('existing resource will not be overwritten: ' + str(target))
+            operations.append(dict(action='link', source=str(source), target=str(target)))
+    if patch_loaders:
+        patch_root = bundle / 'code_support'
+        manifest = json.loads((patch_root / 'loader_patch.json').read_text())
+        for row in manifest['files']:
+            relative = safe_relative(row['path'])
+            source, target = patch_root / relative, code_root / relative
+            if digest(source) != row['new_sha256']:
+                raise ValueError('bundle loader patch hash differs')
+            if target.is_symlink():
+                raise ValueError('refusing to patch a symlink: ' + str(target))
+            if target.exists() and not target.is_file():
+                raise ValueError('refusing to patch a non-file: ' + str(target))
+            current = digest(target) if target.is_file() else None
+            if current == row['new_sha256']:
+                continue
+            if current != row['previous_sha256']:
+                raise ValueError('unknown/local code changes will not be overwritten: ' + str(target))
+            operations.append(dict(action='patch', source=str(source), target=str(target)))
+    return operations
+
+
+def install(bundle, code_root, apply=False, patch_loaders=True):
+    operations = plan_install(bundle, code_root, patch_loaders)
+    for row in operations:
+        print(row['action'].upper(), row['target'], '<-', row['source'])
+    if not apply:
+        print('DRY RUN: nothing changed. Add --apply after checking the paths.')
+        return operations
+    # Validate the entire plan before any writes. Never replace a resource directory.
+    for row in operations:
+        source, target = Path(row['source']), Path(row['target'])
+        target.parent.mkdir(parents=True, exist_ok=True)
+        if row['action'] == 'link':
+            target.symlink_to(source, target_is_directory=True)
+        else:
+            with tempfile.NamedTemporaryFile(dir=target.parent, prefix='.loader_patch-', delete=False) as handle:
+                temporary = Path(handle.name)
+                handle.write(source.read_bytes())
+            if target.exists():
+                temporary.chmod(target.stat().st_mode & 0o777)
+            else:
+                temporary.chmod(0o644)
+            temporary.replace(target)
+    print('ATTACHED. No training, inference, GPU use or upload occurred.')
+    return operations
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('--bundle', type=Path, default=Path(__file__).resolve().parents[1])
+    parser.add_argument('--code-root', type=Path, required=True)
+    parser.add_argument('--apply', action='store_true')
+    parser.add_argument('--no-code-patch', action='store_true')
+    args = parser.parse_args()
+    install(args.bundle, args.code_root, args.apply, not args.no_code_patch)
+
+
+if __name__ == '__main__':
+    main()