# Welcome to FastVideo

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:alt: FastVideo
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:width: 60%
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<p style="text-align:center">
<strong>FastVideo is a lightweight framework for accelerating large video diffusion models.
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<p style="text-align:center">
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<a class="github-button" href="https://github.com/hao-ai-lab/FastVideo/" data-show-count="true" data-size="large" aria-label="Star">Star</a>
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FastVideo is a lightweight framework for accelerating large video diffusion models developed by the [Hao AI Lab](https://hao-ai-lab.github.io/).

<div style="text-align: center;">
  <video controls width="800">
    <source src="https://github.com/user-attachments/assets/79af5fb8-707c-4263-b153-9ab2a01d3ac1" type="video/mp4">
    Your browser does not support the video tag.
  </video>
</div>

FastVideo currently offers: (with more to come)

- [NEW!] [Sliding Tile Attention](https://hao-ai-lab.github.io/blogs/sta/).
- FastHunyuan and FastMochi: consistency distilled video diffusion models for 8x inference speedup.
- First open distillation recipes for video DiT, based on [PCM](https://github.com/G-U-N/Phased-Consistency-Model).
- Support distilling/finetuning/inferencing state-of-the-art open video DiTs: 1. Mochi 2. Hunyuan.
- Scalable training with FSDP, sequence parallelism, and selective activation checkpointing, with near linear scaling to 64 GPUs.
- Memory efficient finetuning with LoRA, precomputed latent, and precomputed text embeddings.

Dev in progress and highly experimental.

## Documentation

% How to start using vLLM?

:::{toctree}
:caption: Getting Started
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getting_started/installation
getting_started/examples/examples_index
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% What is STA Kernel?

:::{toctree}
:caption: Sliding Tile Attention
:maxdepth: 1

sliding_tile_attention/installation
sliding_tile_attention/usage
sliding_tile_attention/test
sliding_tile_attention/demo
:::

:::{toctree}
:caption: Inference
:maxdepth: 1

inference/stepvideo
inference/hunyuanvideo
inference/fasthunyuan
inference/fastmochi
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## Indices and tables

- {ref}`genindex`
- {ref}`modindex`