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.
GodelNumbering · · focus · HN ↗
shriphani · · focus · HN ↗
GodelNumbering · · focus · HN ↗
shriphani · · focus · HN ↗