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Llama-3-Smaug-8B-GGUF

Transformers
GGUF
conversational
Model card Files
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How to use from
llama.cpp
Install (macOS, Linux) 
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
# Run inference directly in the terminal:
llama cli -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
Install from WinGet (Windows) 
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
# Run inference directly in the terminal:
llama cli -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
Use pre-built binary 
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
Build from source code 
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Llama-3-Smaug-8B-GGUF:
Use Docker 
docker model run hf.co/QuantFactory/Llama-3-Smaug-8B-GGUF:
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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

image/png

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

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.

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GGUF
Model size
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Architecture
llama
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Datasets used to train QuantFactory/Llama-3-Smaug-8B-GGUF

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