# Toolformer notes

Created: March 4, 2025 11:42 PM
Tags: tool-use, llm, to-process
Status: In progress

Schick et al. (Meta AI), "Toolformer: Language Models Can Teach Themselves to Use
Tools". NeurIPS 2023.

- Core trick: **self-supervised** — the model annotates its own training data with
  candidate API calls, keeps only the calls that actually reduce perplexity on the
  following tokens, then fine-tunes on that.
- Tools: calculator, Q&A system, search engine, machine translation, calendar.
- No human tool-use annotations needed. That's the whole point.

### Open questions

- How does this compare to prompting-based tool use (ReAct style)? Toolformer bakes
  tool use into weights; ReAct keeps it in-context. Different tradeoff for adding
  new tools later.
- Tool selection at inference is still pretty rigid?

### Aside

- [ ] Untitled
- [ ] Untitled

*Exported from Notion — some blocks may not have transferred.*
