Diffusers documentation


You are viewing main version, which requires installation from source. If you'd like regular pip install, checkout the latest stable version (v0.27.2).
Hugging Face's logo
Join the Hugging Face community

and get access to the augmented documentation experience

to get started


🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you’re looking for a simple inference solution or want to train your own diffusion model, 🤗 Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions.

The library has three main components:

  • State-of-the-art diffusion pipelines for inference with just a few lines of code. There are many pipelines in 🤗 Diffusers, check out the table in the pipeline overview for a complete list of available pipelines and the task they solve.
  • Interchangeable noise schedulers for balancing trade-offs between generation speed and quality.
  • Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.
< > Update on GitHub