Hugging Face is a company that develops tools for building applications using machine learning, especially natural language processing. It is also a platform that allows users to share and collaborate on machine learning models and datasets.
Hugging Face’s mission is “to democratize AI knowledge and assets and to build the future of AI with the community”.
Some of the products and services that Hugging Face offers are:
- Transformers: A Python library that contains open-source implementations of transformer models for text, image, and audio tasks. It is compatible with the PyTorch, TensorFlow and JAX deep learning libraries and includes implementations of notable models like BERT and GPT-2.
- Datasets: A Python library that provides access to over 50,000 datasets for various machine learning tasks, such as text classification, question answering, summarization, etc. It also allows users to load, process, cache, and share their own datasets.
- Spaces: A web-based platform that allows users to create and deploy interactive applications using machine learning models hosted on the Hugging Face Hub. Users can use pre-trained models or upload their own models and use various widgets to create user interfaces.
- Hub: A web-based platform that allows users to host, browse, and collaborate on machine learning models and datasets. Users can upload their own models or use pre-trained models from the community or from Hugging Face’s partners. Users can also use the Hub’s APIs to integrate the models into their applications .
- Compute: A paid service that allows users to deploy their machine learning models on optimized inference endpoints or update their Spaces applications to a GPU in a few clicks. Users can choose from different pricing plans based on their needs.
- Enterprise: A paid service that provides enterprise-grade security, access controls, and dedicated support for teams that want to use Hugging Face’s platform to build AI applications. Users can choose from different pricing plans based on their needs .