Can anyone recommend a great, concise resource to learn LLM technical fundamentals including transformers, pre-training, fine-tuning, etc from the ground up starting with neural networks?<p>The resources I can find are either how to use langchain to write LLM apps, which is not what I want, or very deep graduate level book study, which I don't have the time for.<p>Something that starts with neural networks (which I am familiar with) and takes you all the way to how LLMs work, but as concise as possible.<p>My goal is to be able to talk about LLM technical fundamentals cogently, not necessarily code one from scratch.<p>Thanks!
I'm in the same bot as you are learning with this activeloop course [1].
I think it has a good overview. The problem is that the code is a little bit outdated, which is good because you have to look outside instead of just copy and paste, so you actually know what's going on!<p>[1] <a href="https://learn.activeloop.ai/courses/llms" rel="nofollow">https://learn.activeloop.ai/courses/llms</a>