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Running on Zero
| title: DistillAlign — Autoregressive Video Distillation | |
| emoji: 🎬 | |
| colorFrom: green | |
| colorTo: pink | |
| sdk: gradio | |
| sdk_version: 6.30.0 | |
| app_file: app.py | |
| short_description: Few-step causal text-to-video with a 1.3B student | |
| python_version: "3.12" | |
| startup_duration_timeout: 1h | |
| # 🎬 DistillAlign — Autoregressive Video Distillation | |
| **Coordinating Mode Covering and Mode Seeking in Autoregressive Video Distillation** | |
| This Space runs the released **DistillAlign** generator: a **Wan2.1-T2V-1.3B** student | |
| distilled for few-step *causal* (autoregressive) text-to-video generation. It samples | |
| 21 latent frames in 7 causal blocks with a 4-step DMD schedule (`1000 → 750 → 500 → 250`), | |
| keeps a KV cache across blocks, and streams the latents through the causal Wan VAE — | |
| **81 frames / 480×832 / 16 fps ≈ 5 s** of video. | |
| ## Links | |
| - **Model**: [LiJiaxing/DistillAlign](https://huggingface.co/LiJiaxing/DistillAlign) | |
| - **Code**: [LiJiaxing0213/DistillAlign](https://github.com/LiJiaxing0213/DistillAlign) | |
| - **Paper**: [arXiv 2607.26811](https://huggingface.co/papers/2607.26811) · | |
| [project page](https://lijiaxing0213.github.io/DistillAlign/) | |
| ## Notes | |
| - **Prompt style**: the model was distilled on long, detailed captions. Short prompts | |
| work but detailed multi-sentence descriptions give markedly better results — the | |
| example prompts below are the authors' own evaluation prompts. | |
| - **Speed**: generation takes roughly a minute on the ZeroGPU RTX PRO 6000 | |
| (7 blocks × 4 denoising steps, plus streaming VAE decode). | |
| - **Seed**: set a seed to reproduce a video, or leave `0` for a random one. | |
| - **Checkpoint used**: `checkpoints/distillalign_distill_1p3b_teacher.pt` — the final | |
| joint-distilled 1.3B generator (1.3B DMD teacher), loaded with `strict=True` into a | |
| causal Wan2.1-1.3B wrapper. | |
| ## Credits & licenses | |
| This is a demo wrapper around the authors' code. The example prompts are the authors' | |
| own evaluation prompts from `prompts/distribution_eval_16.txt` in the | |
| [official repository](https://github.com/LiJiaxing0213/DistillAlign) (Apache-2.0). | |
| The DistillAlign code and released weights are Apache-2.0; upstream | |
| [Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B) weights remain subject | |
| to their own license. The causal VAE decoder wrapper follows the | |
| [Self-Forcing](https://github.com/guandeh17/Self-Forcing) (Apache-2.0) implementation. | |