No NVIDIA card, no cloud bill, no course. Just a small model, an afternoon, and one lesson worth more than the training.
I wanted to know what fine-tuning actually takes.
What you actually do, on a normal computer, with no data center and no rented GPU and no credit card.
So one weekend I decided to fine-tune a language model on my Mac. A real one, start to finish, on a desktop.
It worked. It also broke in ways most tutorials never warn you about, which turned out to be the most useful part.
Here is the whole journey, written for someone who has never done this and is not sure they’re allowed to try.
You are allowed.
Let me show you.
First, what “fine-tuning” even means
A language model already knows a lot. It read most of the internet. What it does not know is your specific job.
Fine-tuning is taking that already-smart model and giving it a short, focused apprenticeship on one narrow task until it gets good at that one thing.
Think of hiring a sharp graduate. They can read, write, and reason. They cannot yet fill out your company’s expense form the way your company likes it. You do not re-educate them from birth. You show them fifty…