Thread

1. GodelNumbering · 1790535596 · focus · HN ↗

   This is the golden age of model training. Some days ago, I decided I wanted a local CPU only model that can perform exceptionally well for English to Bash translation (to avoid the googling for command syntax). I got a bunch of subagents to generate large amount of training data (140k+ samples), got the Qwen 3 0.6B base model, pointed Astra at it, and off to the races. It trained for 2 days (on and off) and I got a surprisingly good model for my task! The total active time I spent was a few hours. And it is still improving, what a time to be alive!

   1. amelius · 1790539321 · focus · HN ↗

      I don't understand. If you have a model that can do bash examples already (your subagents), then why would you need to train a model?

      Or are the subagents generating your training data using a closed/paid model?

      1. lp92 · 1790599174 · focus · HN ↗

         You can run a small model locally with very low latency on consumer hardware not to mention the privacy benefits.

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