diffusers and modular-diffusion
Diffusers is a mature, production-ready framework for using pre-built diffusion models at scale, while Modular Diffusion is a lower-level research library for custom model architecture design and training—making them complements that serve different points in the diffusion model development lifecycle.
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 modular-diffusion
cabralpinto/modular-diffusion
Python library for designing and training your own Diffusion Models with PyTorch
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