AI development framework

Hugging Face

Advancing AI accessibility through open source and open science.

Hugging Face is an AI community-building platform that enables the machine learning community to collaborate on models, datasets, and applications. It offers a wide variety of models, datasets, spaces, and solutions that users can browse and use for their work.

With over 400k models and 100k datasets, users can easily create, discover, and collaborate on ML projects. Hugging Face provides open-source Stack, that helps to move faster, explore all modalities, and build a portfolio to showcase your work. Users can share their work with the world and build their ML profile.

Hugging Face provides paid Compute and Enterprise solutions. With Compute solutions, users can deploy optimized inference endpoints or update workspace applications to a GPU in a few clicks, starting at $0.60/hour for GPU. The Enterprise plan, on the other hand, gives users the most advanced platform to build AI with enterprise-grade security, access controls, and dedicated support starting at $20/user/month. It features single Sign-On, Regions, Priority Support, Audit Logs, Resource Groups, and a Private Dataset Viewer.

Hugging Face is used by over 50,000 organizations, including the Allen Institute for AI, Amazon Web Services, Google, Intel, and Microsoft. The platform offers various open-source libraries, including Transformers, Datasets, Tokenizers, and Accelerate, which users can use for computer vision, audio, and natural language processing tasks.

The platform is focused on advancing AI accessibility through open source and open science. Hugging Face offers various resources, including documentation, a blog, a forum, and service status. It has a strong social media presence, with active profiles on GitHub, Twitter, LinkedIn, and Discord.