Hugging Face: the open source AI model platform
Discover Hugging Face, the hub of open source artificial intelligence
Hugging Face is the reference platform of the open source AI community, hosting hundreds of thousands of ready-to-use models, datasets and applications.
Need an audio transcription model, a document classifier or an open source LLM to host on your own infrastructure? Instead of starting from scratch, you start from a proven model, test it online, then deploy it in your environment. It is the go-to reflex of every data team working with open source.
Hugging Face is built around five pillars:
From discovering a model to running it in production, the platform covers the whole chain.
1. The Model Hub: find the right model
A community catalogue where vendors and researchers publish their models, from LLMs to specialised models.
- Search for a model by task: translation, summarisation, vision, audio
- Compare models through detailed model cards and clearly displayed licences
- Try many models directly from your browser
- Follow new releases from the major open source players
- Discover the service here
2. Datasets: ready-to-use data
Thousands of datasets to train, fine-tune or evaluate your models.
- Find annotated data for your domain: text, image, audio
- Benchmark your models against recognised reference datasets
- Version and share your own datasets, privately or publicly
- Document data provenance for your compliance requirements
- Discover the service here
3. Spaces: AI demos and applications
Hosted applications that let you test a model without writing a line of code.
- Try the latest models through interactive demos
- Publish your own demos to validate a use case internally
- Prototype quickly before investing in full development
- Share a link with stakeholders instead of an installation
- Discover the service here
4. Open source libraries: Transformers and its ecosystem
Tools that have become standards for building machine learning projects.
- Load a model in a few lines with the Transformers library
- Fine-tune models on your data with the training tools
- Standardise your pipelines to switch models without rewriting everything
- Build on very active documentation and community support
5. Deployment: from experimentation to production
Hugging Face offers managed services to serve your models without running the infrastructure.
- Deploy a model on managed inference endpoints
- Stay in control: open source models remain deployable in your own cloud
- Govern access to private models and datasets with the enterprise plans
- Size the infrastructure to your real workloads
Planning an open source AI project? turnK helps you choose the right models, fine-tune them on your data and deploy them in a controlled environment. Take a look at our Data & AI services or contact us: our consultants reply within 48 hours.
Les questions les plus fréquentes
Hugging Face is the reference platform for open source artificial intelligence. It hosts hundreds of thousands of models, datasets and applications (Spaces), and maintains libraries such as Transformers that are widely used by data teams.
Primarily data scientists and developers who search for, test and deploy machine learning models. But also companies that want to build on open source models to keep control of their data and costs.
The Model Hub, datasets, Spaces for demos and applications, open source libraries such as Transformers, and managed inference services for production. All with access management for private content.
Most of the platform is free and open source. Paid plans cover advanced accounts, team and enterprise features, and managed inference services billed on usage. Up-to-date pricing is available on the official website.
It depends on your constraints: a proprietary API is faster to deploy, while an open source model gives you more control over data, costs and hosting. turnK helps you decide based on your use cases, volumes and confidentiality requirements.
