121 lines
3.1 KiB
Markdown
121 lines
3.1 KiB
Markdown
(fastvideo-installation)=
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# 🔧 Installation
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FastVideo currently only supports Linux and NVIDIA CUDA GPUs.
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## Requirements
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- **OS: Linux**
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- **Python: 3.10-3.12**
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- **CUDA 12.4**
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- **At least 1 NVIDIA GPU**
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## Set up using Python
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### Create a new Python environment
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#### Conda
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You can create a new python environment using [Conda](https://docs.conda.io/projects/conda/en/stable/user-guide/getting-started.html)
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##### 1. Install Miniconda (if not already installed)
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```bash
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wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
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bash Miniconda3-latest-Linux-x86_64.sh
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source ~/.bashrc
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```
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##### 2. Create and activate a Conda environment for FastVideo
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```bash
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# (Recommended) Create a new conda environment.
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conda create -n fastvideo python=3.12 -y
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conda activate fastvideo
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```
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:::{note}
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[PyTorch has deprecated the conda release channel](https://github.com/pytorch/pytorch/issues/138506). If you use `conda`, please only use it to create Python environment rather than installing packages.
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:::
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#### uv
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:::{tip}
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We highly recommend using `uv` to install FastVideo. In our experience, `uv` speeds up installation by at least 3x.
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:::
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Or you can create a new Python environment using [uv](https://docs.astral.sh/uv/), a very fast Python environment manager. Please follow the [documentation](https://docs.astral.sh/uv/#getting-started) to install `uv`. After installing `uv`, you can create a new Python environment using the following command:
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```console
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# (Recommended) Create a new uv environment. Use `--seed` to install `pip` and `setuptools` in the environment.
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uv venv --python 3.12 --seed
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source .venv/bin/activate
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```
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### Installation
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```bash
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pip install fastvideo
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# or if you are using uv
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uv pip install fastvideo
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```
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Also optionally install flash-attn:
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```bash
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pip install flash-attn==2.7.4.post1 --no-build-isolation
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```
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### Installation from Source
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#### 1. Clone the FastVideo repository
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```bash
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git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo
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```
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#### 2. Install FastVideo
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Basic installation:
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```bash
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pip install -e .
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# or if you are using uv
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uv pip install -e .
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```
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### Optional Dependencies
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#### Flash Attention
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```bash
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pip install flash-attn==2.7.4.post1 --no-build-isolation
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```
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## Set up using Docker
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We also have prebuilt docker images with FastVideo dependencies pre-installed:
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[Docker Images](#docker)
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## Development Environment Setup
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If you're planning to contribute to FastVideo please see the following page:
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[Contributor Guide](#developer-overview)
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## Hardware Requirements
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### For Basic Inference
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- NVIDIA GPU with CUDA 12.4 support
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### For Lora Finetuning
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- 40GB GPU memory each for 2 GPUs with lora
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- 30GB GPU memory each for 2 GPUs with CPU offload and lora
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### For Full Finetuning/Distillation
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- Multiple high-memory GPUs recommended (e.g., H100)
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## Troubleshooting
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If you encounter any issues during installation, please open an issue on our [GitHub repository](https://github.com/hao-ai-lab/FastVideo).
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You can also join our [Slack community](https://join.slack.com/t/fastvideo/shared_invite/zt-2zf6ru791-sRwI9lPIUJQq1mIeB_yjJg) for additional support.
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