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.
This library helps developers and researchers create or use AI models that generate new images, audio, or even molecular structures. You provide text descriptions or existing data, and it outputs novel visual, auditory, or structural content. It's designed for machine learning practitioners and AI artists.
About azula
probabilists/azula
Diffusion models in PyTorch
Azula is a specialized tool that helps machine learning researchers and practitioners generate new, realistic data samples from existing datasets. It takes your raw data, learns its underlying patterns, and then outputs novel data points that resemble the original, such as creating new images or other complex data structures. This is ideal for those working on advanced generative AI.
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