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---
library_name: transformers
license: llama2
datasets:
- aqua_rat
- microsoft/orca-math-word-problems-200k
- m-a-p/CodeFeedback-Filtered-Instruction
- anon8231489123/ShareGPT_Vicuna_unfiltered
---
## Description
This repo contains GGUF format model files for Llama-3-Smaug-8B.
## Files Provided
| Name | Quant | Bits | File Size | Remark |
| -------------------------- | ----- | ---- | --------- | -------------------------------- |
| llama-3-smaug-8b.Q2_K.gguf | Q2_K | 2 | 3.18 GB | 2.96G, +3.5199 ppl @ Llama-3-8B |
| llama-3-smaug-8b.Q3_K.gguf | Q3_K | 3 | 4.02 GB | 3.74G, +0.6569 ppl @ Llama-3-8B |
| llama-3-smaug-8b.Q4_0.gguf | Q4_0 | 4 | 4.66 GB | 4.34G, +0.4685 ppl @ Llama-3-8B |
| llama-3-smaug-8b.Q4_K.gguf | Q4_K | 4 | 4.92 GB | 4.58G, +0.1754 ppl @ Llama-3-8B |
| llama-3-smaug-8b.Q5_K.gguf | Q5_K | 5 | 5.73 GB | 5.33G, +0.0569 ppl @ Llama-3-8B |
| llama-3-smaug-8b.Q6_K.gguf | Q6_K | 6 | 6.60 GB | 6.14G, +0.0217 ppl @ Llama-3-8B |
| llama-3-smaug-8b.Q8_0.gguf | Q8_0 | 8 | 8.54 GB | 7.96G, +0.0026 ppl @ Llama-3-8B |
## Parameters
| path | type | architecture | rope_theta | sliding_win | max_pos_embed |
| ------------------------- | ----- | ---------------- | ---------- | ----------- | ------------- |
| abacusai/Llama-3-Smaug-8B | llama | LlamaForCausalLM | 500000.0 | null | 8192 |
## Benchmarks
# 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](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
### Model Description
- **Developed by:** [Abacus.AI](https://abacus.ai)
- **License:** https://llama.meta.com/llama3/license/
- **Finetuned from model:** [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/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](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. |