[fzzzy]

Well, when Llama 1 came out I signed up and downloaded it, and that led me to llama.cpp. I followed the instructions to quantize the model to fit in my graphics card. Then later when more models like llama2 and mixtral came out I would download and evaluate them.

I kept up on hacker news posts and any comments about things I didn't understand. I've also found the localllama subreddit to be a great way to learn.

Any time I saw a comment on anything I would try it, like ollama, kobold.cpp, sillytavern, textgen-webui, and more.

I also have a friend who has been into ai for many years and we always exchange links to new things. I developed a retrieval augmented generation (rag) app with him and a "transformation engine" pipeline.

So following ai stories on hn and reddit, learning through doing, and applying what I learned to real projects.

[FezzikTheGiant]

Thanks. Very cool. Have you ever tried to implement a transformer from scratch? Like in the Attention is all you need paper? Can a first/second year college student do it

[xyc]

Andrej Karpathy's course is a good resource: https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs...

[fzzzy]

I haven't tried it yet, but I do intend to. I think the code for llm inference is quite straightforward. The complexity lies in collecting the training corpus and doing good rlhf. That's just my intuition.