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Ember-1

589 points · 249 comments · gmays

  1. GodelNumbering · · 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. luisfmh · · focus · HN ↗
      Curious about how you generated the training data? Was it just asking an existing model to generate a bunch of examples?

      I ask cause would this be a kind of model distillation?

      I have a small model I'm looking to train on some data, and I have some real live data but I'd love to be able to extend it.

      1. toasty228 · · focus · HN ↗
        It is a form of distillation, as long as you're working a very narrow "trivial" topics it works perfectly.
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