Hugging Face

Hugging Face is an artificial intelligence company founded in 2016 in New York, United States. It was built to make it easier for developers and organizations to build, share and deploy machine learning models, addressing the difficulty of collaborating on open-source AI tooling, datasets and models across teams.

The platform is organized around a public and private hub for hosting models and datasets, Spaces for running AI applications, and Inference Endpoints for production deployment, supported by open-source libraries such as Transformers and Diffusers. Enterprise customers use private hubs and managed inference for internal AI development; the company reports adoption by more than 50,000 organizations, including large technology firms.

1. Model & dataset hub: hosts more than 2 million models and 500,000 datasets for public or private use.

2. Spaces: lets teams deploy and demo AI applications directly from the hub.

3. Inference Endpoints: provides managed, scalable infrastructure to serve models in production.

4. Open-source libraries: Transformers and Diffusers give standardized APIs for training and inference.

5. Enterprise Hub: adds private repositories, access controls and compute for organizations.

6. Community collaboration: supports versioning, discussions and pull requests on models and datasets.