Release CoCode-World step-4000 LoRA and EMA checkpoint

LICENSE

@@ -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.

README.md

@@ -1,3 +1,57 @@
 ---
 license: apache-2.0
+language:
+- en
+- zh
+base_model: MiniMaxAI/MiniMax-H3
+base_model_relation: adapter
+pipeline_tag: image-to-video
+tags:
+- lora
+- minimax-h3
+- video-generation
+- multi-view
+- world-model
+- decfg
 ---
+
+# CoCode-World Model
+
+The **step-4000** CoCode-World task LoRA for **MiniMax-H3 Ref2VA**, trained on synchronized two-player GTA videos with Proxy555 control. The EMA weights are the ones used by the eight published 60-second evaluation examples.
+
+- **Code and training guide:** https://github.com/IApple233/CoCode-World
+- **Evaluation inputs and results:** https://github.com/IApple233/CoCode-World/tree/main/examples/evaluation
+- **Public training data:** https://huggingface.co/datasets/iapple1/CoCode-World-Data
+- **Project page:** https://iapple233.github.io/CCW/
+
+## Download
+
+```bash
+hf download iapple1/CoCode-World-Model --local-dir checkpoints/step-004000
+```
+
+| File | Use |
+|---|---|
+| `ema.safetensors` | EMA task LoRA; recommended for inference (FP32 storage) |
+| `lora.safetensors` | Non-EMA task LoRA at step 4000 (BF16 storage) |
+| `optimizer.pt`, `rng_state.pt` | Saved training state for an exact optimizer resume with matching training data and configuration |
+| `trainer_state.json` | Architecture, training settings, tensor names fingerprint and payload checksums |
+| `model_manifest.json` | Release provenance and original checkpoint metadata hash |
+
+These are native checkpoint tensors for the provided loader, not a standalone base model or a drop-in Diffusers `load_lora_weights` export. Download the official MiniMax-H3 model separately. Tensor files are unchanged; local paths in the trainer metadata were normalized for publication.
+
+## Training initialization
+
+**First download the official [MiniMax-H3 weights](https://huggingface.co/MiniMaxAI/MiniMax-H3). Then download DiffSynth-Studio's released [Ref2VA DeCFG training adapter](https://www.modelscope.cn/models/DiffSynth-Studio/MiniMax-H3-TrainingAdapter).** Continue task training from that pretrained setup: fuse `model_ref2va.safetensors` into the frozen base at scale 1, then train a fresh rank-64 task LoRA. The training code verifies the exact DeCFG file checksum.
+
+训练前先下载 MiniMax-H3 官方权重，再下载 DiffSynth-Studio 开源的 Ref2VA DeCFG LoRA。训练时固定合入 DeCFG 预设，在此基础上训练 CoCode-World 的 rank-64 任务 LoRA。推理时加载原始 MiniMax-H3 和本仓库的任务 LoRA EMA；不合入训练用 DeCFG 预设。
+
+The published checkpoint was trained with learning rate `1e-5`, 200 warmup steps, rank/alpha `64/64`, EMA decay `0.999`, CP8 × DP4 on 32 GPUs, and a target-row flow-matching objective. See `training_config.json` for the recorded configuration. The original run used 8,552 clips; the public 5,000-clip dataset is a curated subset and does not reproduce the exact original training trajectory.
+
+## Inference
+
+Use the code repository's `scripts/evaluate.sh`. The eight examples include the actual edited first-frame input, all 17 window prompts, original Proxy555 input, seeds, and a compressed preview of the recorded result. Recorded inference used 30 denoising steps, 24 FPS, a 2560 × 720 output, 124-frame windows, 39-frame overlap, and 17 windows cropped to 60 seconds. This is the original task LoRA, not a DMD student.
+
+## License
+
+The task adapter retains this repository's Apache-2.0 license. The MiniMax-H3 base model is separately governed by the [MiniMax-H3 Community License Agreement](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE). The training-only DeCFG adapter retains its upstream terms. No MiniMax-H3 base weights or DeCFG preset weights are redistributed here.

SHA256SUMS.txt

@@ -0,0 +1,9 @@
+f9e2070c247517b1ddf65f7b11b393484a18da91a958fd18a97bd0f241c3125c  LICENSE
+40016785b3089d546b9715e76f6886cbccca98eb3973d4202bd41d6858852bed  README.md
+9d4e0524ee2b9203c2711f2c0b2a133e17d9ea6cb1280aa9974150f0ba7a038c  ema.safetensors
+e0d4a3cb1c8cb8cb8ef36cefeb45ecc164556404f4003ec39b1af8f435ca602c  lora.safetensors
+99c54ce47fe0aa7fa170ddd530b8de7abed0f02dcc970750c63c545021269f33  model_manifest.json
+cfae773db2796b4973eb28d37221eb1ff89f2c3dccdcc09e1a55a2c2b25ff4b1  optimizer.pt
+e4fe9530c60967ab99cab3175013b526f5ec56bbd7e358fe69d9e8f2209f5d71  rng_state.pt
+06a5b4cfdfcd9b6370d8a5930161c8d218ab3835e301bb1d8638c0eeb6d0977b  trainer_state.json
+5af830cdf5c31a04c43031809b795e10dade52708525cb55797553e6f3b92136  training_config.json

ema.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d4e0524ee2b9203c2711f2c0b2a133e17d9ea6cb1280aa9974150f0ba7a038c
+size 1383687680

lora.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e0d4a3cb1c8cb8cb8ef36cefeb45ecc164556404f4003ec39b1af8f435ca602c
+size 691889848

model_manifest.json

@@ -0,0 +1,29 @@
+{
+  "checkpoint_step": 4000,
+  "base_model": "MiniMaxAI/MiniMax-H3",
+  "base_partition": "transformer_ref",
+  "training_preset": "DiffSynth-Studio/MiniMax-H3-TrainingAdapter",
+  "inference_weights": "ema.safetensors",
+  "training_weights": "lora.safetensors",
+  "tensor_files_preserved_byte_for_byte": true,
+  "original_trainer_state_sha256": "e94a5028d85b839114494fbf4105c3025fdc897eeb1074aca1fc6e760ad27b7d",
+  "metadata_normalization": "Only local filesystem paths in trainer_state.json have been replaced with portable paths.",
+  "payloads": {
+    "ema.safetensors": {
+      "bytes": 1383687680,
+      "sha256": "9d4e0524ee2b9203c2711f2c0b2a133e17d9ea6cb1280aa9974150f0ba7a038c"
+    },
+    "lora.safetensors": {
+      "bytes": 691889848,
+      "sha256": "e0d4a3cb1c8cb8cb8ef36cefeb45ecc164556404f4003ec39b1af8f435ca602c"
+    },
+    "optimizer.pt": {
+      "bytes": 1384124083,
+      "sha256": "cfae773db2796b4973eb28d37221eb1ff89f2c3dccdcc09e1a55a2c2b25ff4b1"
+    },
+    "rng_state.pt": {
+      "bytes": 6901,
+      "sha256": "e4fe9530c60967ab99cab3175013b526f5ec56bbd7e358fe69d9e8f2209f5d71"
+    }
+  }
+}

optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cfae773db2796b4973eb28d37221eb1ff89f2c3dccdcc09e1a55a2c2b25ff4b1
+size 1384124083

rng_state.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e4fe9530c60967ab99cab3175013b526f5ec56bbd7e358fe69d9e8f2209f5d71
+size 6901

trainer_state.json

@@ -0,0 +1,90 @@
+{
+  "checkpoint_version": 1,
+  "metadata": {
+    "activation_cpu_offload": true,
+    "adam_betas": [
+      0.9,
+      0.99
+    ],
+    "attention": "full_bidirectional",
+    "audio": "disabled",
+    "context_parallel_degree": 8,
+    "data_parallel_degree": 4,
+    "data_schema": "h3-ref-image-video-splitscreen-cache-v2",
+    "dataset_cursor": 7448,
+    "dataset_epoch": 1,
+    "dataset_manifest": "cache/train/manifest.jsonl",
+    "dataset_manifest_sha256": "8e581827ad4840c721a7771c259ee0fe6b4db7770c9924b87e3deb68be56e8fe",
+    "dataset_text_encoder_hash": "37b3c4f46ff752e9f3ee1a27e146a101ebcf4afda9251fc83eea4f4a23bf5c8a",
+    "dataset_transformer_ref_config_hash": "1d1486b61d9c11b92af41840a4a40b83de8a776db8cc0f4c71b40d4e4371c116",
+    "dataset_vae_config_hash": "76fcd9d9b23b522cd574d1e3adbf138b69f3f6e260e2944e3dbebb4d091cf3ec",
+    "decfg_adapter_conversion_revision": "official-h3-head-role-dim-qkv-split-swiglu-swap-v1",
+    "decfg_adapter_fusion_revision": "bf16-matmul-add-like-diffsynth-preset-v1",
+    "decfg_adapter_model_id": "DiffSynth-Studio/MiniMax-H3-TrainingAdapter",
+    "decfg_adapter_path": "models/DiffSynth-Studio/MiniMax-H3-TrainingAdapter/model_ref2va.safetensors",
+    "decfg_adapter_release_revision": "bdddb151d0dfb62b1dfa9e2f8ae6a6e1b179e098",
+    "decfg_adapter_scale": 1.0,
+    "decfg_adapter_sha256": "9361683349c1bf78f206c382d91b1e01b91fcddc2408e85ab39c9faa51f0d3d1",
+    "decfg_adapter_usage": "frozen_training_preset_excluded_from_task_lora_and_inference",
+    "depth_control": "removed",
+    "ema_decay": 0.999,
+    "epoch_tail_policy": "continuous_global_sample_stream",
+    "global_samples_seen": 16000,
+    "global_world_size": 32,
+    "gradient_accumulation": 1,
+    "learning_rate": 1e-05,
+    "lora_alpha": 64.0,
+    "lora_rank": 64,
+    "lora_targets": "qkvo-ffn",
+    "lr_schedule": "linear_warmup_then_constant",
+    "max_gradient_norm": 1.0,
+    "model_root": "models/MiniMax-H3",
+    "objective": "target_rows_h3_flow_velocity_mse",
+    "reference_audio": "disabled",
+    "reference_image_frozen": true,
+    "reference_kinds": [
+      "image",
+      "video"
+    ],
+    "reference_noise_aug": 0.999,
+    "reference_order": "target_first_frame_then_proxy_video",
+    "sample_order_revision": "epoch-buffer-shuffle-seed-plus-epoch-v1",
+    "seed": 42,
+    "shuffle_buffer_size": 32768,
+    "split_screen": "agent_000_left_agent_001_right",
+    "target_canvas": [
+      736,
+      2560
+    ],
+    "text_encoder_execution_revision": "qwen3vl-hidden50-hook-layer49-inference-retain-0-through-49-v2",
+    "text_encoder_layer": 50,
+    "time_distribution": "uniform_noise_ratio_then_shift",
+    "transformer_partition": "transformer_ref",
+    "transformer_ref_config_hash": "1d1486b61d9c11b92af41840a4a40b83de8a776db8cc0f4c71b40d4e4371c116",
+    "video_shift": 12.0,
+    "warmup_steps": 200,
+    "weight_decay": 0.0
+  },
+  "parameter_names_sha256": "ba3f0ddd1e25c79475e81da156f0b15f9caf6ecbc7e4675b526c99c925526231",
+  "payloads": {
+    "ema.safetensors": {
+      "bytes": 1383687680,
+      "sha256": "9d4e0524ee2b9203c2711f2c0b2a133e17d9ea6cb1280aa9974150f0ba7a038c"
+    },
+    "lora.safetensors": {
+      "bytes": 691889848,
+      "sha256": "e0d4a3cb1c8cb8cb8ef36cefeb45ecc164556404f4003ec39b1af8f435ca602c"
+    },
+    "optimizer.pt": {
+      "bytes": 1384124083,
+      "sha256": "cfae773db2796b4973eb28d37221eb1ff89f2c3dccdcc09e1a55a2c2b25ff4b1"
+    },
+    "rng_state.pt": {
+      "bytes": 6901,
+      "sha256": "e4fe9530c60967ab99cab3175013b526f5ec56bbd7e358fe69d9e8f2209f5d71"
+    }
+  },
+  "step": 4000,
+  "trainable_parameters": 345899008,
+  "trainable_tensors": 624
+}

training_config.json

@@ -0,0 +1,62 @@
+{
+  "activation_cpu_offload": true,
+  "adam_betas": [
+    0.9,
+    0.99
+  ],
+  "attention": "full_bidirectional",
+  "audio": "disabled",
+  "context_parallel_degree": 8,
+  "data_parallel_degree": 4,
+  "data_schema": "h3-ref-image-video-splitscreen-cache-v2",
+  "dataset_manifest_sha256": "8e581827ad4840c721a7771c259ee0fe6b4db7770c9924b87e3deb68be56e8fe",
+  "dataset_text_encoder_hash": "37b3c4f46ff752e9f3ee1a27e146a101ebcf4afda9251fc83eea4f4a23bf5c8a",
+  "dataset_transformer_ref_config_hash": "1d1486b61d9c11b92af41840a4a40b83de8a776db8cc0f4c71b40d4e4371c116",
+  "dataset_vae_config_hash": "76fcd9d9b23b522cd574d1e3adbf138b69f3f6e260e2944e3dbebb4d091cf3ec",
+  "decfg_adapter_conversion_revision": "official-h3-head-role-dim-qkv-split-swiglu-swap-v1",
+  "decfg_adapter_fusion_revision": "bf16-matmul-add-like-diffsynth-preset-v1",
+  "decfg_adapter_model_id": "DiffSynth-Studio/MiniMax-H3-TrainingAdapter",
+  "decfg_adapter_path": "models/DiffSynth-Studio/MiniMax-H3-TrainingAdapter/model_ref2va.safetensors",
+  "decfg_adapter_release_revision": "bdddb151d0dfb62b1dfa9e2f8ae6a6e1b179e098",
+  "decfg_adapter_scale": 1.0,
+  "decfg_adapter_sha256": "9361683349c1bf78f206c382d91b1e01b91fcddc2408e85ab39c9faa51f0d3d1",
+  "decfg_adapter_usage": "frozen_training_preset_excluded_from_task_lora_and_inference",
+  "depth_control": "removed",
+  "ema_decay": 0.999,
+  "epoch_tail_policy": "continuous_global_sample_stream",
+  "global_samples_seen": 16000,
+  "global_world_size": 32,
+  "gradient_accumulation": 1,
+  "learning_rate": 1e-05,
+  "lora_alpha": 64.0,
+  "lora_rank": 64,
+  "lora_targets": "qkvo-ffn",
+  "lr_schedule": "linear_warmup_then_constant",
+  "max_gradient_norm": 1.0,
+  "model_root": "models/MiniMax-H3",
+  "objective": "target_rows_h3_flow_velocity_mse",
+  "reference_audio": "disabled",
+  "reference_image_frozen": true,
+  "reference_kinds": [
+    "image",
+    "video"
+  ],
+  "reference_noise_aug": 0.999,
+  "reference_order": "target_first_frame_then_proxy_video",
+  "sample_order_revision": "epoch-buffer-shuffle-seed-plus-epoch-v1",
+  "seed": 42,
+  "shuffle_buffer_size": 32768,
+  "split_screen": "agent_000_left_agent_001_right",
+  "target_canvas": [
+    736,
+    2560
+  ],
+  "text_encoder_execution_revision": "qwen3vl-hidden50-hook-layer49-inference-retain-0-through-49-v2",
+  "text_encoder_layer": 50,
+  "time_distribution": "uniform_noise_ratio_then_shift",
+  "transformer_partition": "transformer_ref",
+  "transformer_ref_config_hash": "1d1486b61d9c11b92af41840a4a40b83de8a776db8cc0f4c71b40d4e4371c116",
+  "video_shift": 12.0,
+  "warmup_steps": 200,
+  "weight_decay": 0.0
+}