Keep standalone H3 LoRA checkpoint and matching video examples
Browse files- NOTICE +1 -1
- README.md +45 -38
- SHA256SUMS +7 -24
- examples/cartoon-studio.mp4 +2 -2
- examples/crystal-heart.mp4 +2 -2
- examples/river.mp4 +2 -2
- examples/tokyo-car.mp4 +2 -2
- infer.py +5 -17
- merged_config.json +0 -24
- transformer/config.json +0 -26
- transformer/diffusion_pytorch_model-00001-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00002-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00003-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00004-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00005-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00006-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00007-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00008-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00009-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00010-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00011-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00012-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00013-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model-00014-of-00014.safetensors +0 -3
- transformer/diffusion_pytorch_model.safetensors.index.json +0 -645
NOTICE
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MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
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This repository provides modified
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The inference utilities contain modified Apache-2.0 code. Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. See CODE_LICENSE for the code license. The checkpoint remains subject to LICENSE.
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MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
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This repository provides a modified adapter and custom inference integration; it is not the unchanged official MiniMax-H3 base checkpoint.
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The inference utilities contain modified Apache-2.0 code. Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. See CODE_LICENSE for the code license. The checkpoint remains subject to LICENSE.
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README.md
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base_model: MiniMaxAI/MiniMax-H3
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tags:
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- minimax-h3
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- text-to-audio-video
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license: other
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license_name: minimax-h3-community-license-agreement
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license_link: LICENSE
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---
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# MiniMax-H3 3-Step
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**
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**中文：LoRA
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## Quick start
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Use Python 3.12 and a compatible CUDA-enabled PyTorch environment.
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The tested environment uses PyTorch 2.11.0/CUDA 13.0; `requirements.txt` pins
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A high-memory GPU is required; consumer-GPU offloading and quantization are not validated.
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```bash
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hf download Perflow-Shuai/MiniMax-H3-3Step-LoRA --local-dir ./h3-3step
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--exclude "adapter_model.safetensors"
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hf download MiniMaxAI/MiniMax-H3 \
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--revision fa9c8ab1eaa21c8ae25e7e40b83b2e6002f340af \
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--local-dir ./h3-base
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cd h3-3step
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pip install -r requirements.txt
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python infer.py --base ../h3-base --
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--output ./output --seed 20262020
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```
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Output: `output/video.mp4`,
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**中文：
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## Python integration
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```python
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from h3_inference import load_base, ChunkedH3Runtime, ChunkGeometry, generate_sample
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model = load_base("/path/to/h3-3step")
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runtime = ChunkedH3Runtime(model, checkpoint_blocks=False)
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video_rows, audio_rows = generate_sample(
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runtime, ChunkGeometry(), {"prompt_embeds": prompt_embeds},
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`prompt_embeds` is the positive H3 text-encoder output **before** the token refiner,
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shape `[1, text_length, text_dim]`. See `infer.py` for text encoding and VAE decoding,
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and `inference_config.json` for
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The current interface is first-clip text-to-audio/video, not long-video continuation.
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## Video cases
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These videos
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so outputs can change in composition and are not pixel-identical to separate FP32 adapter inference.
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### Tokyo night drive / 东京夜间行车
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非叙事音乐（non_diegetic_music）：不适用（N/A）。
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## Optional standalone adapter
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The original adapter remains available for users who specifically need it:
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208 attention/feed-forward groups have rank **256**, and 58 other projection groups have rank **128**;
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alpha equals rank (effective scale 1). There are 266 groups / 532 FP32 tensors.
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See `adapter_config.json` for the exact rank pattern.
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It is not a standard PEFT package; use the included loader on the **unmodified** H3 transformer.
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**Do not apply the adapter to the merged weights.** The default quick-start does not download or load it.
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## Terms
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Built with MiniMax-H3.
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and acceptable-use requirements, applies. See [NOTICE](NOTICE).
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Inference code is covered by [CODE_LICENSE](CODE_LICENSE).
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base_model: MiniMaxAI/MiniMax-H3
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tags:
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- minimax-h3
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- lora
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- text-to-audio-video
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license: other
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license_name: minimax-h3-community-license-agreement
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license_link: LICENSE
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---
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# MiniMax-H3 3-Step LoRA
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**One standalone LoRA checkpoint: `adapter_model.safetensors`. No H3 base weights are included.**
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**中文：这是单个独立 LoRA checkpoint，不是主模型权重。加载原版 H3，再加载这一个文件即可，不需要同时加载多个 LoRA。**
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## Checkpoint / Rank
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| Projection groups | Rank | Alpha | Effective scale |
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| --- | --- | --- | --- |
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| 208 attention / feed-forward groups | 256 | 256 | 1 |
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| 58 input / conditioning / modulation / output groups | 128 | 128 | 1 |
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- 266 groups, 532 FP32 tensors, approximately 7.54 GB.
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- Exact per-group ranks are in `adapter_config.json`.
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- Keys: `<projection>.lora_a` and `<projection>.lora_b`.
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- Keep adapter factors and residual calculations in FP32; do not cast the entire adapted model to BF16/FP16.
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- SHA-256: `f7f720c3622880919047eb013750749dcff114b502d1ec5f19159eb962bed192`.
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**中文：不是统一 rank；208 组 rank 256，58 组 rank 128，scale 均为 1。**
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## Quick start
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Use Python 3.12 and a compatible CUDA-enabled PyTorch environment.
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The tested environment uses PyTorch 2.11.0/CUDA 13.0; `requirements.txt` pins Diffusers.
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A high-memory GPU is required; consumer-GPU offloading and quantization are not validated.
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```bash
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hf download Perflow-Shuai/MiniMax-H3-3Step-LoRA --local-dir ./h3-3step
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hf download MiniMaxAI/MiniMax-H3 \
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--revision fa9c8ab1eaa21c8ae25e7e40b83b2e6002f340af \
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--local-dir ./h3-base
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cd h3-3step
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pip install -r requirements.txt
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python infer.py --base ../h3-base --adapter . \
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--prompt-file examples/tokyo-car.txt --output ./output --seed 20262020
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```
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Output: `output/video.mp4`, with generated stereo audio.
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Use the **original, unmodified H3 base**. The script attaches this single adapter automatically;
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do not additionally merge or load another copy of it.
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If upgrading from an earlier download, use a fresh `h3-3step` directory and a new output directory.
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Generation is 1344×768, 124 frames at 24 FPS, with 32 kHz stereo audio.
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The sampler uses **3 evaluations per chunk**, 8 chunks (**24 evaluations per clip**), CFG 1.
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This is not equivalent to simply setting a stock H3 pipeline to three steps.
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Rerun the same command and output directory to resume an interrupted clip.
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**中文：原版 H3 + 本仓库这一个 LoRA + 配套三步分块采样器。视频下面保留完整英文 Prompt 和中文翻译，实际输入使用英文。**
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## Python integration
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```python
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from h3_inference import load_base, load_adapter, ChunkedH3Runtime, ChunkGeometry, generate_sample
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model = load_adapter(load_base("/path/to/h3-base"), "/path/to/h3-3step")
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runtime = ChunkedH3Runtime(model, checkpoint_blocks=False)
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video_rows, audio_rows = generate_sample(
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runtime, ChunkGeometry(), {"prompt_embeds": prompt_embeds},
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`prompt_embeds` is the positive H3 text-encoder output **before** the token refiner,
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shape `[1, text_length, text_dim]`. See `infer.py` for text encoding and VAE decoding,
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and `inference_config.json` for chunk boundaries and paired audio/video schedules.
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This checkpoint is not a standard PEFT package. Use the included loader, which handles
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variable ranks, Q/K/V splitting and feed-forward layout; do not assume an arbitrary
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`load_lora_weights()` call or ComfyUI LoRA node supports it unchanged.
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The current interface is first-clip text-to-audio/video, not long-video continuation.
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## Video cases
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These four videos use the **standalone adapter on the original H3 base**, with the
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included 3-step-per-chunk sampling protocol.
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### Tokyo night drive / 东京夜间行车
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非叙事音乐（non_diegetic_music）：不适用（N/A）。
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## Terms
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Built with MiniMax-H3. The [MiniMax-H3 Community License Agreement](LICENSE), including
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its territory restrictions and acceptable-use requirements, applies. See [NOTICE](NOTICE).
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Inference code is covered by [CODE_LICENSE](CODE_LICENSE).
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No base-model weights are distributed in the current release.
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c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4 CODE_LICENSE
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22e7eff12c0438035158f4af110db27939f628631799ecf267908aae67110e3e requirements.txt
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f7f720c3622880919047eb013750749dcff114b502d1ec5f19159eb962bed192 adapter_model.safetensors
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4228e6046b4c4bc5ff19918b1478fe480a2d2e32d9a4f302907e4829dbe35e10 adapter_config.json
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2c941cb261e8b0336b9381bbca48f6ca2445afb9339dd6297628249d6c4d3c8f merged_config.json
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548009ce03fa4d3f5dc0222d951dd7f0aa43b63891b1adfb6e8d5cc31d38c62e h3_inference/__init__.py
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4b0834210b2371d876bdd9f755d249e1607771f439e2daab5455d669a3a3e80f h3_inference/adapter.py
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862f9b9a14efa1093093c516ac5d4395f93880fd4dd505a27f68804642612d17 h3_inference/geometry.py
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fc069f0f7135d5fcff9091e34b58c70e4572508d45e9b5fb08043c62ef99eb9e h3_inference/runtime.py
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b503e4b1df08f934f2e9742799a8de0189f7df4da6ff228237f59feaa8ef1544 h3_inference/sampler.py
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c1a8fd348a5fc50dcd721c4e6d539c7279401dc6e3739d8d64503946c52d13f8 transformer/diffusion_pytorch_model-00001-of-00014.safetensors
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37a16a7676e6d57941958cd7d7547e7f8d6dc1188b0c53a18bba748a75c84a86 transformer/diffusion_pytorch_model-00004-of-00014.safetensors
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f6ddf8a641724020ce1e3cd947a6b8b924ec4d64905c2534d6602076aa7d77cb transformer/diffusion_pytorch_model-00005-of-00014.safetensors
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32851ed8d340ac58960c9f1d7ba2913cb93536aac4e93fcd6437ce7d572da1d9 transformer/diffusion_pytorch_model-00006-of-00014.safetensors
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a11a33e514f7a08e45cd4590f63da46ab97e1edf1df5657799a2f1723761a748 transformer/diffusion_pytorch_model-00007-of-00014.safetensors
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c9ed2676d8ebc00acf4d5a14d684e07053e2c62ac8370e02d84261814745dfa5 transformer/diffusion_pytorch_model-00008-of-00014.safetensors
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a1636c40a984eb55ea9a139b480a63133b2bf98f0a14adc6545539c11c022869 transformer/diffusion_pytorch_model-00010-of-00014.safetensors
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f4c5b4f89db79b677f09ff24b5ebe3dfa9789678ad5feea5d806a0d4965266e5 transformer/diffusion_pytorch_model-00011-of-00014.safetensors
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008a5792314c630348b0735a36dda79e6a507ed99c0d50c6a8fbe8aa381520ea transformer/diffusion_pytorch_model-00013-of-00014.safetensors
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accf3ecd92bb61e7a20592ace4821ae36daab8a7f758f0209482ba58a72afc88 transformer/diffusion_pytorch_model-00014-of-00014.safetensors
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036fa8b98389121db8b623033726ae1abbca209a35a6be18198aa24ec40d8a84 examples/tokyo-car.txt
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f25bdc348449700841b53d86141767a1dc7d9c6a15d166b2917d4b415853a0dc examples/tokyo-car.zh.txt
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04570ba05295155a8d9ef350fbe3af62c6a1b5a7d01411ac7509c62d700acb3d examples/cartoon-studio.txt
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e0b8a927daf1595536196b7a7cccfe85ecbec6a994db39f6802677e150789235 examples/cartoon-studio.zh.txt
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f2f2946d4cbae0044a59652da5bfb867c9a485a3f874bebb00cc7e0169541f76 examples/river.txt
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f9f2841a4a142dea834954f218bb61974e938b879b1eeb7b3db3318c3c440237 examples/river.zh.txt
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1734e62c01c9b18dbfa9379c556284790ec9e84bed2c344f54b79b409784eb70 examples/crystal-heart.txt
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b08cfe13f972c39f97c155170ea058b87bb0c528ada82479cec433f069cef805 examples/crystal-heart.zh.txt
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e41a25a1598722dfbf6723f97ff765d378bd844f43850f8c28ce750c4855006a NOTICE
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c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4 CODE_LICENSE
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12594c1f285dcdc47f12dff991ce88757e338634f99e69a4755900afb5154066 infer.py
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4228e6046b4c4bc5ff19918b1478fe480a2d2e32d9a4f302907e4829dbe35e10 adapter_config.json
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4b0834210b2371d876bdd9f755d249e1607771f439e2daab5455d669a3a3e80f h3_inference/adapter.py
|
| 12 |
862f9b9a14efa1093093c516ac5d4395f93880fd4dd505a27f68804642612d17 h3_inference/geometry.py
|
| 13 |
fc069f0f7135d5fcff9091e34b58c70e4572508d45e9b5fb08043c62ef99eb9e h3_inference/runtime.py
|
| 14 |
b503e4b1df08f934f2e9742799a8de0189f7df4da6ff228237f59feaa8ef1544 h3_inference/sampler.py
|
| 15 |
b4b1f8b476e170899fbf4d7c258975bbf9a0ddcaa8faa0f9b4852683eaba112d h3_inference/media.py
|
| 16 |
+
fb482584a4a7d7d2e9fbf4682f607f20422878fa6e5ee6716b5178eb5378ffed examples/tokyo-car.mp4
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| 17 |
036fa8b98389121db8b623033726ae1abbca209a35a6be18198aa24ec40d8a84 examples/tokyo-car.txt
|
| 18 |
f25bdc348449700841b53d86141767a1dc7d9c6a15d166b2917d4b415853a0dc examples/tokyo-car.zh.txt
|
| 19 |
+
4190950baaf4951b2f47b2dcf58c566a18c038943ed7f84c72b32a4dd9d18d0d examples/cartoon-studio.mp4
|
| 20 |
04570ba05295155a8d9ef350fbe3af62c6a1b5a7d01411ac7509c62d700acb3d examples/cartoon-studio.txt
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| 21 |
e0b8a927daf1595536196b7a7cccfe85ecbec6a994db39f6802677e150789235 examples/cartoon-studio.zh.txt
|
| 22 |
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b3cc80e3545be9312c6823dfcc02704d6e80c1a79248ec69eb9494cbbb2ed4d8 examples/river.mp4
|
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f2f2946d4cbae0044a59652da5bfb867c9a485a3f874bebb00cc7e0169541f76 examples/river.txt
|
| 24 |
f9f2841a4a142dea834954f218bb61974e938b879b1eeb7b3db3318c3c440237 examples/river.zh.txt
|
| 25 |
+
115527cbe1ecea84297c980664ea84d5d5038d0b626b83cc48697b12a0b14fd7 examples/crystal-heart.mp4
|
| 26 |
1734e62c01c9b18dbfa9379c556284790ec9e84bed2c344f54b79b409784eb70 examples/crystal-heart.txt
|
| 27 |
b08cfe13f972c39f97c155170ea058b87bb0c528ada82479cec433f069cef805 examples/crystal-heart.zh.txt
|
examples/cartoon-studio.mp4
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:4190950baaf4951b2f47b2dcf58c566a18c038943ed7f84c72b32a4dd9d18d0d
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+
size 863194
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examples/crystal-heart.mp4
CHANGED
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@@ -1,3 +1,3 @@
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| 1 |
version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 3590526
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examples/river.mp4
CHANGED
|
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:b3cc80e3545be9312c6823dfcc02704d6e80c1a79248ec69eb9494cbbb2ed4d8
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size 2442555
|
examples/tokyo-car.mp4
CHANGED
|
@@ -1,3 +1,3 @@
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| 1 |
version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 3191451
|
infer.py
CHANGED
|
@@ -45,8 +45,7 @@ def encode_prompt(base, prompt):
|
|
| 45 |
def main():
|
| 46 |
parser = argparse.ArgumentParser()
|
| 47 |
parser.add_argument('--base', required=True, type=Path)
|
| 48 |
-
parser.add_argument('--
|
| 49 |
-
parser.add_argument('--adapter', type=Path, help='Optional unmerged adapter; use with --transformer pointing to the original base')
|
| 50 |
parser.add_argument('--prompt-file', required=True, type=Path)
|
| 51 |
parser.add_argument('--output', required=True, type=Path)
|
| 52 |
parser.add_argument('--seed', type=int, default=20262020)
|
|
@@ -68,18 +67,9 @@ def execute(args):
|
|
| 68 |
torch.backends.cudnn.allow_tf32 = False
|
| 69 |
torch.use_deterministic_algorithms(True)
|
| 70 |
prompt = args.prompt_file.read_text().strip()
|
| 71 |
-
|
| 72 |
-
if args.adapter is not None and merged_config.exists():
|
| 73 |
-
raise ValueError('Do not apply an adapter on top of already merged weights')
|
| 74 |
-
if args.adapter is None:
|
| 75 |
-
config = json.loads(merged_config.read_text())
|
| 76 |
-
weight_identity = config['weights_sha256']
|
| 77 |
-
else:
|
| 78 |
-
config = json.loads((args.adapter / 'adapter_config.json').read_text())
|
| 79 |
-
weight_identity = config['adapter_sha256']
|
| 80 |
identity = hashlib.sha256(json.dumps({'prompt':prompt, 'seed':args.seed,
|
| 81 |
-
'
|
| 82 |
-
'base':str(args.base.resolve()),
|
| 83 |
'nfe':3, 'width':1344, 'height':768}, sort_keys=True).encode()).hexdigest()
|
| 84 |
checkpoint = args.output / 'chunk_state.safetensors'
|
| 85 |
resume = None
|
|
@@ -87,7 +77,7 @@ def execute(args):
|
|
| 87 |
with safe_open(checkpoint, framework='pt', device='cpu') as handle:
|
| 88 |
metadata = handle.metadata()
|
| 89 |
if metadata['identity'] != identity:
|
| 90 |
-
raise ValueError('Output directory belongs to another prompt/seed/
|
| 91 |
saved = load_file(str(checkpoint))
|
| 92 |
resume = int(metadata['block']), saved['video'], saved['audio'], saved['rng']
|
| 93 |
complete = args.output / 'COMPLETE.json'
|
|
@@ -110,9 +100,7 @@ def execute(args):
|
|
| 110 |
else:
|
| 111 |
condition = encode_prompt(args.base, prompt)
|
| 112 |
atomic_tensors(condition_path, condition, {'identity': identity})
|
| 113 |
-
model = load_base(str(args.
|
| 114 |
-
if args.adapter is not None:
|
| 115 |
-
model = load_adapter(model, args.adapter)
|
| 116 |
runtime = ChunkedH3Runtime(model, checkpoint_blocks=False)
|
| 117 |
|
| 118 |
def save_chunk(block, video, audio, rng):
|
|
|
|
| 45 |
def main():
|
| 46 |
parser = argparse.ArgumentParser()
|
| 47 |
parser.add_argument('--base', required=True, type=Path)
|
| 48 |
+
parser.add_argument('--adapter', type=Path, default=Path(__file__).resolve().parent)
|
|
|
|
| 49 |
parser.add_argument('--prompt-file', required=True, type=Path)
|
| 50 |
parser.add_argument('--output', required=True, type=Path)
|
| 51 |
parser.add_argument('--seed', type=int, default=20262020)
|
|
|
|
| 67 |
torch.backends.cudnn.allow_tf32 = False
|
| 68 |
torch.use_deterministic_algorithms(True)
|
| 69 |
prompt = args.prompt_file.read_text().strip()
|
| 70 |
+
config = json.loads((args.adapter / 'adapter_config.json').read_text())
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 71 |
identity = hashlib.sha256(json.dumps({'prompt':prompt, 'seed':args.seed,
|
| 72 |
+
'adapter_sha256':config['adapter_sha256'], 'base':str(args.base.resolve()),
|
|
|
|
| 73 |
'nfe':3, 'width':1344, 'height':768}, sort_keys=True).encode()).hexdigest()
|
| 74 |
checkpoint = args.output / 'chunk_state.safetensors'
|
| 75 |
resume = None
|
|
|
|
| 77 |
with safe_open(checkpoint, framework='pt', device='cpu') as handle:
|
| 78 |
metadata = handle.metadata()
|
| 79 |
if metadata['identity'] != identity:
|
| 80 |
+
raise ValueError('Output directory belongs to another prompt/seed/base/adapter')
|
| 81 |
saved = load_file(str(checkpoint))
|
| 82 |
resume = int(metadata['block']), saved['video'], saved['audio'], saved['rng']
|
| 83 |
complete = args.output / 'COMPLETE.json'
|
|
|
|
| 100 |
else:
|
| 101 |
condition = encode_prompt(args.base, prompt)
|
| 102 |
atomic_tensors(condition_path, condition, {'identity': identity})
|
| 103 |
+
model = load_adapter(load_base(str(args.base)), args.adapter)
|
|
|
|
|
|
|
| 104 |
runtime = ChunkedH3Runtime(model, checkpoint_blocks=False)
|
| 105 |
|
| 106 |
def save_chunk(block, video, audio, rng):
|
merged_config.json
DELETED
|
@@ -1,24 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"format": "diffusers-transformer",
|
| 3 |
-
"adapter_required": false,
|
| 4 |
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| 20 |
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},
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"precision": "native BF16/FP32",
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"base_model": "MiniMaxAI/MiniMax-H3",
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"base_revision": "fa9c8ab1eaa21c8ae25e7e40b83b2e6002f340af"
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transformer/config.json
DELETED
|
@@ -1,26 +0,0 @@
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{
|
| 2 |
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"_class_name": "MiniMaxH3Transformer3DModel",
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