(fastvideo-installation)= # 🔧 Installation FastVideo currently only supports Linux and CUDA GPUs. The code is tested on Python 3.10.0 and CUDA 12.4, primarily with NVIDIA H100 GPUs. ## Prerequisites - CUDA 12.4 installed and supported - Linux operating system ## Installation Options ### Option 1: Quick Install ```bash pip install fastvideo ``` ### Option 2: Installation from Source #### 1. Install Miniconda (if not already installed) ```bash wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh bash Miniconda3-latest-Linux-x86_64.sh source ~/.bashrc ``` #### 2. Create and activate a Conda environment for FastVideo ```bash conda create -n fastvideo python=3.10 -y conda activate fastvideo ``` #### 3. Clone the FastVideo repository ```bash git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo ``` #### 4. Install FastVideo Basic installation: ```bash pip install -e . ``` ## Optional Dependencies ### Flash Attention ```bash pip install flash-attn==2.7.0.post2 --no-build-isolation ``` ### Sliding Tile Attention (STA) To try Sliding Tile Attention (optional), please follow the instructions in [csrc/sliding_tile_attention/README.md](#sta-installation) to install STA. ## Development Environment Setup If you're planning to contribute to FastVideo please see the following page: [Contributor Guide](#developer-guide) ## Hardware Requirements ### For Basic Inference - NVIDIA GPU with CUDA support - Minimum 20GB VRAM for quantized models (e.g., single RTX 4090) ### For Lora Finetuning - 40GB GPU memory each for 2 GPUs with lora - 30GB GPU memory each for 2 GPUs with CPU offload and lora ### For Full Finetuning/Distillation - Multiple high-memory GPUs recommended (e.g., H100) ## Troubleshooting If you encounter any issues during installation, please open an issue on our [GitHub repository](https://github.com/hao-ai-lab/FastVideo). You can also join our [Slack community](https://join.slack.com/t/fastvideo/shared_invite/zt-2zf6ru791-sRwI9lPIUJQq1mIeB_yjJg) for additional support.