Replacing my best friends with an LLM trained on 500,000 group chat messages (via) Izzy Miller used a 7 year long group text conversation with five friends from college to fine-tune LLaMA, such that it could simulate ongoing conversations. They started by extracting the messages from the iMessage SQLite database on their Mac, then generated a new training set from those messages and ran it using code from the Stanford Alpaca repository. This is genuinely one of the clearest explanations of the process of fine-tuning a model like this I’ve seen anywhere.
Recent articles
- Video + notes on upgrading a Datasette plugin for the latest 1.0 alpha, with help from uv and OpenAI Codex CLI - 6th November 2025
- Code research projects with async coding agents like Claude Code and Codex - 6th November 2025
- A new SQL-powered permissions system in Datasette 1.0a20 - 4th November 2025