Hugging Face

Hugging Face is a platform where the machine learning community can collaborate on models, datasets, and applications. It aims to advance and democratize artificial intelligence through open source and open science. Users can create, discover, and collaborate on ML projects, hosting unlimited public models, datasets, and applications.

The platform supports various modalities including text, image, video, audio, and 3D. It provides an open-source stack to help users move faster in their ML development. Hugging Face also offers paid services such as Team & Enterprise solutions for organizations, Inference Providers for accessing models through a unified API, and Compute options for deploying on optimized GPUs.

Over 400,000 organizations reportedly use Hugging Face. The company focuses on building the foundation of ML tooling with the community.

Best for

• Machine learning engineers and researchers looking to share and discover models.
• Developers needing access to a wide range of public datasets.
• Teams requiring a collaborative platform for ML projects with enterprise features.
• Individuals building an ML portfolio by sharing their work.
• Organizations seeking compute resources for model deployment and inference.

Frequently asked questions

What types of machine learning assets can I find on Hugging Face?

You can find models, datasets, and applications across various modalities like text, image, video, audio, and 3D.

Does Hugging Face offer paid services?

Yes, Hugging Face offers paid services including Team & Enterprise solutions, Inference Providers for model access, and Compute options for GPU deployment.

How many organizations use Hugging Face?

The website states that more than 400,000 organizations use Hugging Face.

Is Hugging Face focused on open source?

Yes, Hugging Face emphasizes open source and open science, building the foundation of ML tooling with the community.

Can I deploy models directly on Hugging Face?

Yes, you can deploy models using their Compute services, which include options for optimized GPUs.

Alternatives

• GitHub Copilot – Pick this for an AI assistant that integrates directly into your coding environment across editors, CLI, and GitHub.