diffusers and stable-diffusion-cpp-python

Diffusers provides high-level PyTorch APIs for running diffusion models, while stable-diffusion-cpp-python offers CPU-optimized C++ inference bindings as an alternative backend for users prioritizing speed and resource efficiency over the broader model variety that Diffusers supports.

diffusers
90
Verified
Maintenance 25/25
Adoption 15/25
Maturity 25/25
Community 25/25
Maintenance 10/25
Adoption 9/25
Maturity 18/25
Community 14/25
Stars: 33,029
Forks: 6,832
Downloads:
Commits (30d): 82
Language: Python
License: Apache-2.0
Stars: 104
Forks: 13
Downloads:
Commits (30d): 0
Language: Python
License: MIT
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About diffusers

huggingface/diffusers

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

Provides modular, composable building blocks—including interchangeable noise schedulers, pretrained models, and end-to-end pipelines—enabling both quick inference and custom system design via the Hugging Face Model Hub. Emphasizes transparency and customizability over abstraction, allowing developers to inspect and modify individual diffusion components rather than treating them as black boxes.

About stable-diffusion-cpp-python

william-murray1204/stable-diffusion-cpp-python

stable-diffusion.cpp bindings for python

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