diffusers and azula
Diffusers is a mature, production-ready framework that provides pre-built pipelines and model implementations, while Azula is a lower-level research library focused on core diffusion model components and theory—making them complementary tools where Azula could be used to build custom diffusion models that Diffusers then packages and deploys at scale.
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 azula
probabilists/azula
Diffusion models in PyTorch
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