---
license: mit
---

# JAX-Diffusion

JAX-Diffusion is a project that implements diffusion models using JAX, a high-performance numerical computing library. Diffusion models are a class of generative models that have gained popularity for their ability to generate high-quality data samples.

## Features

- Implementation of diffusion models in JAX.
- High-performance and scalable computations.
- Modular and extensible codebase.

## Installation

1. Clone the repository:
   ```bash
   git clone https://github.com/your-username/JAX-Diffusion.git
   cd JAX-Diffusion
   ```

2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```

## Usage

To train a diffusion model:
```bash
python train.py --config configs/default.yaml
```

To generate samples:
```bash
python generate.py --model checkpoints/model.pth
```

## Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Submit a pull request with a clear description of your changes.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Acknowledgments

- [JAX](https://github.com/google/jax) for providing the foundation for numerical computing.
- The research community for advancements in diffusion models.