Zoyd
/

Text Generation
Transformers
Safetensors
llama
conversational
text-generation-inference
Inference Endpoints
exl2
Edit model card
Configuration Parsing Warning: In config.json: "quantization_config.bits" must be an integer

Exllamav2 quant (exl2 / 4.25 bpw) made with ExLlamaV2 v0.0.21

Other EXL2 quants:

Quant Model Size lm_head
2.2
20886 MB
6
2.5
23192 MB
6
3.0
27273 MB
6
3.5
31356 MB
6
3.75
33398 MB
6
4.0
35434 MB
6
4.25
37456 MB
6
5.0
43598 MB
6
6.0
51957 MB
8
6.5
56014 MB
8
8.0
60211 MB
8

Smaug-Llama-3-70B-Instruct

Built with Meta Llama 3

image/png

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.

The model outperforms Llama-3-70B-Instruct substantially, and is on par with GPT-4-Turbo, on MT-Bench (see below).

EDIT: Smaug-Llama-3-70B-Instruct is the top open source model on Arena-Hard currently! It is also nearly on par with Claude Opus - see below.

We are conducting additional benchmark evaluations and will add those when available.

Model Description

Evaluation

Arena-Hard

Score vs selected others (sourced from: (https://lmsys.org/blog/2024-04-19-arena-hard/#full-leaderboard-with-gpt-4-turbo-as-judge))

Model Score 95% Confidence Interval Average Tokens
GPT-4-Turbo-2024-04-09 82.6 (-1.8, 1.6) 662
Claude-3-Opus-20240229 60.4 (-3.3, 2.4) 541
Smaug-Llama-3-70B-Instruct 56.7 (-2.2, 2.6) 661
GPT-4-0314 50.0 (-0.0, 0.0) 423
Claude-3-Sonnet-20240229 46.8 (-2.1, 2.2) 552
Llama-3-70B-Instruct 41.1 (-2.5, 2.4) 583
GPT-4-0613 37.9 (-2.2, 2.0) 354
Mistral-Large-2402 37.7 (-1.9, 2.6) 400
Mixtral-8x22B-Instruct-v0.1 36.4 (-2.7, 2.9) 430
Qwen1.5-72B-Chat 36.1 (-2.5, 2.2) 474
Command-R-Plus 33.1 (-2.1, 2.2) 541
Mistral-Medium 31.9 (-2.3, 2.4) 485
GPT-3.5-Turbo-0613 24.8 (-1.6, 2.0) 401

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, and more information will be released later on. For now, see the previous Smaug paper: https://arxiv.org/abs/2402.13228.

Downloads last month
6
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Datasets used to train Zoyd/abacusai_Smaug-Llama-3-70B-Instruct-4_25bpw_exl2