A Python library for wiring diffusion models into image, video and audio applications.
Start with an idea
Prototype a text-to-image feature in your own app with a selected model and repeatable parameters.
Build a masked image-editing workflow that replaces selected regions and compares the results.
The documentation supplies code, input masks and generated example images. These are publisher examples, not our test results.
Official inpainting walkthroughBefore you begin
Python + model pipeline
Linux · Windows · macOS with supported PyTorch hardware
The real tradeoffs
No library license fee; compute is your responsibility.
Local GPU time, rented GPUs and any hosted inference endpoint can cost money. Some gated models require an account and accepted terms.
Apache-2.0
Read the code licenseVaries by checkpoint
Diffusers is a library, not a single permissively licensed model. Review the chosen model card and its terms.
Follow the evidence
Official sources were reviewed on October 14, 2026. We did not install, run or benchmark this project. This is a source-check date, not a release date.
library purpose tasks
Apache-2.0
model loading gated models optimization
Python and PyTorch setup
masked editing examples unmasked-area caveat
Links and project terms can change. These sources document the claims above; they are not a safety certification. Read our full method.