I’m new to the field of large language models (LLMs) and I’m really interested in learning how to train and use my own models for qualitative analysis. However, I’m not sure where to start or what resources would be most helpful for a complete beginner. Could anyone provide some guidance and advice on the best way to get started with LLM training and usage? Specifically, I’d appreciate insights on learning resources or tutorials, tips on preparing datasets, common pitfalls or challenges, and any other general advice or words of wisdom for someone just embarking on this journey.
Thanks!
I’m also interested, so I hope you don’t mind me joining the ride. Personally, I’d like a self hosted tool, but am happy to see what the community says.
If you just want to use a local llm, using something like gpt4all is probably the easiest. Oobabooga or llama.cpp for a more advanced route.
I use ollama with llama3 on my macbook with open-webui and it works real nice. Mistral7b is another one I like. On my PC I have been using oobabooga with models I get from huggingface and I use it as an api for hobby projects.
I have never trained models, I don’t have the vram. My GPU is pretty old so I just use these for random gamedev and webdev projects and for messing around with RP in sillytavern.
I managed to get ollama running through Docker easily. It’s by far the least painful of the options I tried, and I just make requests to the API it exposes. You can also give it GPU resources through Docker if you want to, and there’s a CLI tool for a quick chat interface if you want to play with that. I can get LLAMA 3 (8B) running on my 3070 without issues.
Training a LLM is very difficult and expensive. I don’t think it’s a good place for anyone to start. Many of the popular models (LLAMA, GPT, etc) are astronomically expensive to train and require and ungodly number of resources.
yep, definitely agree with all of this.
Using LM Studio would be even easier to get started
Unfortunately, I don’t expect it to remain free forever.