metadata

library_name: transformers
license: llama2
datasets:
  - aqua_rat
  - microsoft/orca-math-word-problems-200k
  - m-a-p/CodeFeedback-Filtered-Instruction
  - anon8231489123/ShareGPT_Vicuna_unfiltered

QuantFactory/Llama-3-Smaug-8B-GGUF

This is quantized version of abacusai/Llama-3-Smaug-8B created using llama.cpp

Original Model Card

Llama-3-Smaug-8B

Built with Meta Llama 3

This model was built using the Smaug recipe for improving performance on real world multi-turn conversations applied to meta-llama/Meta-Llama-3-8B-Instruct.

Model Description

Developed by: Abacus.AI
License: https://llama.meta.com/llama3/license/
Finetuned from model: meta-llama/Meta-Llama-3-8B-Instruct.

Evaluation

MT-Bench

########## First turn ##########
                   score
model             turn
Llama-3-Smaug-8B 1   8.77500
Meta-Llama-3-8B-Instruct 1   8.31250
########## Second turn ##########
                   score
model             turn
Meta-Llama-3-8B-Instruct 2   7.8875 
Llama-3-Smaug-8B 2   7.8875
########## Average ##########
                 score
model
Llama-3-Smaug-8B  8.331250
Meta-Llama-3-8B-Instruct 8.10

Model	First turn	Second Turn	Average
Llama-3-Smaug-8B	8.78	7.89	8.33
Llama-3-8B-Instruct	8.31	7.89	8.10

This version of Smaug uses new techniques and new data compared to Smaug-72B, and more information will be released later on. For now, see the previous Smaug paper: https://arxiv.org/abs/2402.13228.