this post was submitted on 07 May 2024
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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!

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[–] Zworf@beehaw.org 17 points 6 months ago* (last edited 6 months ago) (14 children)

Training your own will be very difficult. You will need to gather so much data to get a model that has basic language understanding.

What I would do (and am doing) is just taking something like llama3 or mistral and adding your own content using RAG techniques.

But fair play if you do manage to train a real model!

[–] BaroqueInMind@lemmy.one 3 points 6 months ago (13 children)

OLlama is so fucking slow. Even with a 16-core overclocked Intel on 64Gb RAM with an Nvidia 3080 10Gb VRAM, using a 22B parameter model, the token generation for a simple haiku takes 20 minutes.

[–] xcjs@programming.dev 5 points 6 months ago (1 children)

No offense intended, but are you sure it's using your GPU? Twenty minutes is about how long my CPU-locked instance takes to run some 70B parameter models.

On my RTX 3060, I generally get responses in seconds.

[–] kiku123@feddit.de 3 points 6 months ago

I agree. My 3070 runs the 8B Llama3 model in about 250ms, especially for short responses.

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