Comment by professoretc
2 days ago
I saw "Hugginface" listed alongside C++, React, and SQL as skills on a resume recently. Wasn't quite sure what to make of that.
2 days ago
I saw "Hugginface" listed alongside C++, React, and SQL as skills on a resume recently. Wasn't quite sure what to make of that.
Honestly it's a large enough library with enough weirdness and untested areas, footguns, and bugs that I'd deem it just as valid as React for example.
Why did tensor_parallel have output += mod instead of output = output + mod? (The += breaks backprop). Nobody tested it! A user had to notice it was broken and make a PR!
For an uni course I tried to fine tune Gemma in a few days, it wasn't easy because tutorials often were written with old version of hf libraries that now work differently, there's a lot of areas to improve, everything still seems kinda fresh and so it's a pain in the ass to deviate from simple walkthroughs to something tailored to your needs.
I've found I benefit most from AI when I ask it questions about technical topics, like programming or using a device like a synthesizer or DAW software. There's pshychological effect I get especially when I get an answer that says "that feature is not supported". I get the feeling that it's not my fault that something feels very difficult, I know WHY it is difficult when somebody tells me there is no easy way to do what you want, so I don't waste any more time trying to find the solution. I must look elsewhere then.
So I wonder, trying to learn AI and how to use it, shouldn't the AI itself be the best guide for understanding AI? Maybe not so much with the latest research or latest products, because AI is not yet trained on those, but sooner or later AI should feel as easy a subject as say JavaScript programming.