Hugging Face

Accelerate is an open-source library from Hugging Face that makes PyTorch training code run on any hardware and in distributed setups with minimal changes — including mixed precision and FSDP and DeepSpeed support.

Diffusers is an open-source Python library by Hugging Face for using and training diffusion models for image, video and audio generation. It is built on PyTorch and is structured into pipelines, models and schedulers.

Datasets is an open-source Python library from Hugging Face for loading, processing and sharing machine-learning datasets. It uses Apache Arrow and memory-mapping to handle even very large amounts of data efficiently.

Hugging Face Spaces is a hosting platform for deploying and sharing interactive machine learning applications without your own server infrastructure. Apps become usable directly in the browser, for example via Gradio, Streamlit, Docker or static HTML.

Hugging Face is the central platform of the open-source AI community — a hub for models, datasets, and demos, and the maintainer of widely used libraries like Transformers, Diffusers, and PEFT.

Central platform for openly shared AI models, datasets and demos — a kind of GitHub for machine-learning artifacts.

Open-source Python library from Hugging Face that gives unified access to thousands of pretrained models across text, vision and audio.