96 lines
2.2 KiB
Markdown
96 lines
2.2 KiB
Markdown
(fastvideo-installation)=
|
|
|
|
# 🔧 Installation
|
|
|
|
FastVideo currently only supports Linux and NVIDIA CUDA GPUs.
|
|
|
|
FastVideo has been tested on the following GPUs, but it should work on any GPUs that supports CUDA 12.4+, please create an issue if you discover any issues:
|
|
- RTX 4090
|
|
- A40
|
|
- L40S
|
|
- A100
|
|
- H100
|
|
|
|
## Requirements
|
|
|
|
- OS: Linux
|
|
- Python: 3.10-3.12
|
|
- CUDA 12.4+
|
|
|
|
## Installation Options
|
|
|
|
### Option 1: Quick Install
|
|
|
|
```bash
|
|
pip install fastvideo
|
|
```
|
|
|
|
### Option 2: Installation from Source
|
|
|
|
We recommend using a Python environment such as Conda.
|
|
|
|
#### 1. [Optional] 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. [Optional] 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==2.7.4.post1 --no-build-isolation
|
|
```
|
|
|
|
### Sliding Tile Attention (STA) (Requires CUDA 12.4+ and H100)
|
|
|
|
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-overview)
|
|
|
|
## 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.
|