Open-source AI projects built with Hugging Face.
The framework most LLM applications are still assembled from.
Speech recognition that holds up on accents, noise and 90+ languages.
The data framework for connecting models to your own sources.
A text-to-speech toolkit with voice cloning from seconds of audio.
Wrap any model in a shareable web UI in a few lines.
Fine-tune a hundred different models from one interface.
Twelve build areas, from chatbots and agents to vector search and fine-tuning.
Retrieval-augmented generation — grounding a model in your own documents and data.
5 projectsThe scaffolding around a model: UI builders, experiment tracking and app frameworks.
5 projectsRunning models fast and cheaply: local runtimes, inference servers and OpenAI-compatible APIs.
4 projectsEmbedding stores and similarity search — the memory layer under most RAG systems.
3 projectsConversational apps you can actually ship — chat UIs, assistants and the plumbing behind them.
2 projectsProjects where the model plans, calls tools and works a task through to a result on its own.
2 projectsDiffusion pipelines, node graphs and browser front-ends for generating and editing images.
2 projectsSpeech recognition, text-to-speech and voice cloning you can run yourself.
2 projectsDetection, segmentation and tracking — the frameworks real vision products are built on.
2 projectsAdapting an existing model to your data — LoRA, full fine-tunes and the tooling around them.
2 projectsWiring models into multi-step processes that run without a human in the loop.
2 projectsSeveral specialised agents co-ordinating on one job — roles, hand-offs and shared state.
2 projects
