# TinyLM Swarm Lab

- **Event:** [Google I/O Hackathon](https://cerebralvalley.ai/e/google-io-hackathon)
- **When:** Sat, May 23 at 9:00 AM – 10:00 PM (PDT)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Ethan Zemelman](https://cerebralvalley.ai/u/ethanzemelman)
- **GitHub:** https://github.com/Zemelware/TinyLM-Swarm-Lab
- **Demo video:** https://drive.google.com/file/d/1KfzhOo1UVWTn1SVoDUs1Lvy8dha3lOX-/view?usp=sharing
- **Gallery:** https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery/28

TinyLM Swarm Lab is a local mission-control app for running tiny language-model research experiments. The local orchestrator uses Gemini 3.5 Flash to generate experiment hypotheses, then assigns independent workers to test different tiny-LM configurations. Each worker runs real training code, produces artifacts like config.json, metrics.json, notes.md, train.log, and checkpoint.json, and reports results back to the dashboard.

The project solves the manual loop of small-model experimentation: choosing hypotheses, launching runs, reading logs, comparing metrics, and deciding what to try next. TinyLM Swarm Lab makes that process visible and repeatable by showing the active worker fleet, current best model, efficiency trade-offs, artifact outputs, and checkpoint-based sampling in one UI.

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Markdown version of https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery/28. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt