Base or Instruct version of LLM for fine tuning?

Beginners
1

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…

2

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,

  1. Create a test set.
  2. Start with prompting a model.
  3. Do the same with different models.
  4. Fine-tune the best-performing model. Test the FT model.

Good luck.
Sahar

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