abacusai
/

Smaug-Llama-3-70B-Instruct

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 ---
 library_name: transformers
+license: llama2
+datasets:
+- aqua_rat
+- microsoft/orca-math-word-problems-200k
+- m-a-p/CodeFeedback-Filtered-Instruction
 ---
+# Llama-3-Smaug-8B
+### Built with Meta Llama 3
+This model was built using a new Smaug recipe  for improving performance on real world multi-turn conversations applied to
+[meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct).
+The model outperforms Llama-3-70B-Instruct substantially, and is on par with GPT-4-Turbo, on MT-Bench (see below).
 ### Model Description
+- **Developed by:** [Abacus.AI](https://abacus.ai)
+- **License:** https://llama.meta.com/llama3/license/
+- **Finetuned from model:** [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct).
 ## Evaluation
+### MT-Bench
+```
+########## First turn ##########
+                   score
+model             turn
+Smaug-Llama-3-70B-Instruct         1     9.40000
+GPT-4-Turbo                        1     9.37500
+Meta-Llama-3-70B-Instruct          1     9.21250
+########## Second turn ##########
+                   score
+model             turn
+Smaug-Llama-3-70B-Instruct         2     9.0125
+GPT-4-Turbo                        2     9.0000
+Meta-Llama-3-70B-Instruct          2     8.8000
+########## Average ##########
+                 score
+model
+Smaug-Llama-3-70B-Instruct          9.206250
+GPT-4-Turbo                         9.187500
+Meta-Llama-3-70B-Instruct           9.006250
+```
+| Model | First turn | Second Turn | Average |
+| :---- | ---------: | ----------: | ------: |
+| Smaug-Llama-3-70B-Instruct  | 9.40 | 9.01 | 9.21 |
+| GPT-4-Turbo | 9.38 |  9.00 | 9.19 |
+| Meta-Llama-3-70B-Instruct | 9.21 |  8.80 | 9.01 |
+This version of Smaug uses new techniques and new data compared to [Smaug-72B](https://huggingface.co/abacusai/Smaug-72B-v0.1), and more information will be released later on. For now, see the previous Smaug paper: https://arxiv.org/abs/2402.13228.