🧪Thinking Machines Lab - Tinker
thinking-machines-lab/tinker-cookbook
Post-training with Tinker
⭐ Popular: 4k stars, gaining about 48 a week
View on GitHub ↗repo profile
momentum
durability
bus factor = how many people it takes to cover more than half the commits (6 months). 1 is a solo project; higher means the work is spread across a team. top-author share is the single busiest author's slice of those commits.
since we covered it
why it's a big deal
- Brings structure to the chaotic world of model fine-tuning and evaluation.
- Helps small teams and researchers build custom LLMs without reinventing training loops.
- Promotes reproducibility through clean, composable code examples and shared configs.
under the hood
- Apache-2.0 licensed.
- Recipes for SFT, RLHF, preference optimization, RAG fine-tuning, and synthetic data generation.
- Built for integration with the Tinker API (currently in early access) and Hugging Face datasets.
our take from PR#19, 2025-10-15
star history
- PR#19 1k 2025-10-15
- now 4k + 3k since first covered
curve is sampled from GitHub's star history, plus our own daily readings since we covered it; the dashed stretch is before we first covered it, the solid line since. figures at coverage are the numbers we printed then (approx.), current count is live.
understory
Output and attention are roughly in balance.
- output, commits & releases
- clout, star velocity
output = commits & releases; clout = star velocity, both 0 to 100 monthly indices; the gap where output runs above clout is the understory. The understory →
covered in
-
Tinker, Cookbook of fine-tuning recipes built on the Tinker API
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