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!
I didn't have a local GPU, so I asked it to go out and find hardware. It found a google TPU v6e which seemed reasonably priced. I gave it my google api key. I told it to use TPU only when training and bring it down afterwards. That's about it.
I've done this sort of thing before but with Vast. Pre-deposited some money online, then let the LLM request and manage a training run on an allocation. Worked pretty well without risking bankruptcy.
GodelNumbering · · focus · HN ↗
shriphani · · focus · HN ↗
GodelNumbering · · focus · HN ↗
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This is the part where the narrator looks at the camera and says "Don't try this at home, kids!"
hgoel · · focus · HN ↗