Llama-3-8B-Instruct-vector-diff

Llama-3 chat vector

• Update 0426: A small problem with the deployment of the model 'Llama-3-Seagull-Evo-8B', but we hope to have it back in good time!
• Update 0526: Check our newest EMM model, Alpha-Ko-8B-Instruct

This is 'modelified' version of chat vector from the paper Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages. So this is not a model, its just weight diff, just for ease to use myself(or you too)!

What I understand here: 'Chat vector method' is a merging method that utilizes the difference between the base model, the continuously pre-trained (usually language transferred) model, and the chat model; so the recipe is

model(base) + weight_diff(continous pretrained) + weight_diff(instruct) or

model(base) + weight_diff(continous pretrained + fine-tuned) + weight_diff(instruct).

So before (my) initial purpose in comparing which method is better, llama3 → CP + chat vector → FT vs. llama3 → CP → FT + chat vector, it seems reasonable to compare it with other methods in Mergekit.

All that aside, I'd like to thank @beomi for creating such an awesome korean-based model.