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!
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.
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.
I agree. My 3070 runs the 8B Llama3 model in about 250ms, especially for short responses.
Hmmm weird. I have a 4090 / Ryzen 5800X3D and 64GB and it runs really well. Admittedly it’s the 8B model because the intermediate sizes aren’t out yet and 70B simply won’t fly on a single GPU.
But it really screams. Much faster than I can read. PS: Ollama is just llama.cpp under the hood.
Edit: Ah, wait, I know what’s going wrong here. The 22B parameter model is probably too big for your VRAM. Then it gets extremely slow yes.
What is the appropriate size for 10Gb VRAM?