Instructions to use vanzl/DiffusionART-HunyuanVideo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vanzl/DiffusionART-HunyuanVideo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vanzl/DiffusionART-HunyuanVideo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add paper citation
Browse files
README.md
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Subject to the [Tencent Hunyuan Community License](https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/blob/main/LICENSE.txt)
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and [Notice](https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/blob/main/Notice).
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Training provenance and weight hashes are recorded in [release.json](https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/blob/main/release.json).
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Subject to the [Tencent Hunyuan Community License](https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/blob/main/LICENSE.txt)
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and [Notice](https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/blob/main/Notice).
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Training provenance and weight hashes are recorded in [release.json](https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/blob/main/release.json).
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## Citation
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```bibtex
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@misc{wan2026diffusionartefficientstablescalable,
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title={DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models},
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author={Zhenglin Wan and Jiayu Chen and Zhengfeiyang Zhang and Pengfei Zhou and Wangbo Zhao and Fangyuan Kong and Pengfei Wan and Kun Gai and Yang You},
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year={2026},
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eprint={2610.12572},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2610.12572},
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}
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```
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