# Welcome to FastVideo

FastVideo is an inference and post-training framework for video diffusion models. One pipeline covers data preprocessing, fine-tuning, distillation, and inference. Attention backends, parallelism, and quantization are separate modules, so you can add one without changing model code.

## Key Features

FastVideo has the following features:

- End-to-end post-training support for bidirectional and autoregressive models
  - Full finetuning and LoRA [finetuning](training/finetune.md) for state-of-the-art open video DiTs
  - [Data preprocessing pipeline](training/data_preprocess.md) for video, image, and text data
  - [Distribution Matching Distillation (DMD2)](distillation/dmd.md) stepwise distillation
  - Sparse attention with [Video Sparse Attention](attention/vsa/index.md)
  - [Sparse distillation](https://hao-ai-lab.github.io/blogs/fastvideo_post_training/) to achieve >50x denoising speedup
  - [Attn-QAT training](training/attn_qat.md) for quantization-aware post-training
  - Causal distillation through Self-Forcing
  - Scalable training with FSDP2, sequence parallelism, and selective activation checkpointing
  - See the [training overview](training/overview.md) for the full training workflow
- State-of-the-art performance optimizations for inference
  - Sequence parallelism for distributed inference
  - Multiple state-of-the-art [attention backends](attention/index.md)
  - User-friendly [CLI](inference/cli.md) and Python API
  - See the [support matrix](inference/support_matrix.md) for supported models and [optimizations](inference/optimizations.md) for the full list
- Realtime video generation and editing
  - [Dreamverse](https://github.com/hao-ai-lab/FastVideo/tree/main/apps/dreamverse): stream and "vibe direct" video in realtime ([live demo](https://dreamverse.fastvideo.org/))

## Documentation

Welcome to FastVideo! This documentation will help you get started with our unified inference and post-training framework for accelerated video generation.

Use the navigation menu on the left to explore different sections:

- **Getting Started**: Installation and quick start guides
- **Inference**: Learn how to use FastVideo for video generation
- **Training**: Data preprocessing and fine-tuning workflows
- **Distillation**: Post-training optimization techniques
- **Sliding Tile Attention**: Legacy workflow docs and kernel notes
- **Video Sparse Attention**: Efficient attention for video models
- **Design**: Framework architecture and design principles
- **Developer Guide**: Contributing and development setup
- **API Reference**: Complete API documentation