Diffusers
Hugging FaceDiffusers is a PyTorch library from Hugging Face providing pretrained diffusion models for generating images, audio, and 3D molecular structures. It offers ready-to-use inference pipelines, interchangeable noise schedulers, and pretrained models that serve as building blocks for custom diffusion systems. It is Hugging Face's primary library for diffusion-based generative models.
Verified 2026-08-13 via GitHub and the LICENSE body.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core-gated
- ungated
LICENSE file is the standard, unmodified Apache 2.0 text. The repository is public and unarchived, and the README describes the whole library with no paid, enterprise or hosted tier beside it, so source is public and the core ungated.
- https://github.com/huggingface/diffusers/blob/main/LICENSE recorded 2026-08-13
LICENSE file is the verbatim Apache License Version 2.0 text
- https://api.github.com/repos/huggingface/diffusers recorded 2026-08-13
Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch main - for huggingface/diffusers.
- https://raw.githubusercontent.com/huggingface/diffusers/main/README.md recorded 2026-08-13
README describes the three core components - pipelines, schedulers and pretrained models - as the whole toolbox. No paid tier or feature-gated build appears.
Adoption
4 high confidence8,248,209 PyPI downloads of `diffusers` in the trailing 30 days, which falls in the 1M-10M a month band of the software usage scale, level 4.
- https://pypistats.org/api/packages/diffusers/recent recorded 2026-08-13
last_month downloads = 8,248,209 for diffusers
Capability
4 high confidenceDeep but domain-specific to diffusion/generative models rather than general-purpose ML.
- https://github.com/huggingface/diffusers recorded 2026-08-13
README still describes pipelines, interchangeable schedulers and pretrained diffusion models for image, audio and 3D generation
Verified 2026-08-13