# autodistill Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/autodistill
> Markdown URL: https://aitinkerers.org/technologies/autodistill.md
> Technology record last updated: 2026-02-24T01:34:58Z
> Generated: 2026-08-25T19:10:50Z

- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [autodistill - an open source framework for model distillation](https://sf.aitinkerers.org/talks/rsvp_bkDN_zUQGV4)

autodistill is an open source framework for distilling big, general, slower models into domain-specific, smaller, and faster models. Right now, it best supports computer vision tasks. With autodistill, users apply foundation models like SAM and CLIP to auto label datasets and train smaller models in fewer than 10 lines of code. Hackers want to adapt foundation models to domain-specific models that they own, often leveraging their proprietary data. autodistill presents one open source approach to this.

- Event context: 🤖🔄🧠 AI Tinkerers SF - August Meetup — 2023-08-10 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_bkDN_zUQGV4

## Related Technologies

- [CLIP](https://aitinkerers.org/technologies/clip) ([Markdown](https://aitinkerers.org/technologies/clip.md)) — 10 public demos
- [Foundation models](https://aitinkerers.org/technologies/foundation-models) ([Markdown](https://aitinkerers.org/technologies/foundation-models.md)) — 5 public demos
- [OpenAI](https://aitinkerers.org/technologies/openai) ([Markdown](https://aitinkerers.org/technologies/openai.md)) — 111 public demos
- [SAM](https://aitinkerers.org/technologies/sam) ([Markdown](https://aitinkerers.org/technologies/sam.md)) — 1 public demo