| 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. | |