Hugging Face
| Introduction: | Hugging Face is the leading platform for the machine learning community to collaborate on, discover, and build with AI models, datasets, and applications, advancing open source and open science in artificial intelligence. |
| Recorded in: | 6/12/2025 |
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What is Hugging Face?
Hugging Face is a comprehensive platform designed to democratize and advance artificial intelligence through open source and open science. It serves as a central hub where the global machine learning community can discover, share, host, and collaborate on a vast ecosystem of pre-trained models, datasets, and AI applications (Spaces). The platform provides the necessary infrastructure and open-source tools, such as the Transformers library, to accelerate ML development across various modalities including text, image, video, audio, and 3D. It caters to individual researchers, developers, and large enterprises, offering both free public collaboration features and paid compute and enterprise solutions for advanced needs like secure deployment, dedicated support, and enhanced access controls.
How to use Hugging Face
Users can get started by exploring the extensive catalog of over 1 million models, 400,000 AI applications (Spaces), and 250,000 datasets directly on the platform. To contribute, host, or collaborate on ML projects, users need to sign up for an account. The platform offers free access for public models, datasets, and applications, fostering open collaboration. For more demanding needs, Hugging Face provides paid compute solutions, including Inference Endpoints for optimized model deployment and GPU upgrades for Spaces applications, starting at $0.60/hour. Additionally, enterprise-grade solutions are available, starting at $20/user/month, offering features like Single Sign-On, regional deployments, priority support, audit logs, resource groups, and private dataset viewing, enabling teams to build AI with enhanced security and control.
Hugging Face's core features
Hosting and sharing of unlimited public machine learning models
Hosting and sharing of unlimited public datasets
Hosting and sharing of unlimited public AI applications (Spaces)
Access to a vast library of over 1 million pre-trained models
Access to over 400,000 community-built AI applications
Access to over 250,000 datasets for various ML tasks
Support for diverse ML modalities including text, image, video, audio, and 3D
Provision of open-source ML libraries and tools (e.g., Transformers, Diffusers, Datasets)
Paid compute solutions for model deployment (Inference Endpoints) and accelerated application execution (GPU for Spaces)
Enterprise features like SSO, priority support, audit logs, and private resource management
Use cases of Hugging Face
Researchers publishing and sharing their latest machine learning models and research findings
Developers deploying AI-powered applications and demos quickly using Hugging Face Spaces
Data scientists discovering, sharing, and versioning large-scale datasets for training ML models
Companies building and managing private AI models and datasets with enterprise-grade security and access controls
Students and enthusiasts learning about and experimenting with state-of-the-art AI technologies
Teams collaborating on complex machine learning projects in a centralized environment
Individuals showcasing their machine learning portfolio and contributions to the AI community
Organizations leveraging pre-trained models for various tasks like natural language processing, computer vision, and audio generation
Developers integrating powerful ML capabilities into their own applications using Hugging Face's open-source libraries
AI practitioners fine-tuning large language models with parameter-efficient techniques (PEFT)