[philipkglass]

The weights are just numbers. I don't what technical background you have in other areas of computing, but I think that this is a good, short introduction that doesn't assume too much:

https://www.3blue1brown.com/lessons/mini-llm/

To quote part of it, Training a model can be thought of as tuning the dials on a really big machine. The way that a language model behaves is entirely determined by these many different continuous values, usually called parameters or weights.

Longer and slightly more technical, "Intro to Large Language Models" by Andrej Karpathy:

https://www.youtube.com/watch?v=zjkBMFhNj_g

[MoonWalk]

Thanks for the reply. I've been programming professionally since the '90s (no background in ML or neural networks and whatnot), and I realize that the weights are numbers. So I was asking whether different weight sets can be applied to a model at will.

I'm really just trying to get a handle on the different layers so I can set up an environment and put it to work for limited coding assistance. For my purposes, I think an all-local setup is the best way for me to learn and should be enough for the coding tasks I have in mind. Mainly I want to automate tedious tasks away, like "modify these Swift classes' members and JSON deserialization routines to match what's coming out of my server API."

Thanks for the link! Reading it right now... and yes, this looks great. Appreciate it.