Base or Instruct version of LLM for fine tuning?
Can I please ask if Base version or Instruct version is right choice for fine tuning LLM model?For example, I use the LLM model for multiple text classification. Should I choose Llama3.1 8b or Llama3.1 8b Instruct?And can this be generalized to other models? Like for Gemma2 9b vs Gemma2 9b Instruct, Mistral 7b vs Mistral 7b Instruct, Mistral-Nemo-Base-2407 vs Mistral-Nemo-Instruct-2407 and so on…It’s not clear to me from the documentation…
2024-08-08T11:32:58Z
TL;DR Use the instructional version of the models.As Always - It depends; Mostly on your resources and expectations.In most cases, ppl who don’t require domain adaptation or significant differences in alignment - will want to work with the Instruct version, for LLaMA or any other LLM.For example,Prompting isn’t a thing on the base version, and you’ll need to use few-shot and other techniques to get the model to understand what you want.Using Instruct versions allowing you to achieve almost anything with a prompt, but you get stuck in this “ping-pong UX”.In your case, for multiple-text classification,Create a test set.Start with prompting a model.Do the same with different models.Fine-tune the best-performing model. Test the FT model.Good luck.Sahar