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GPTQ commit model & tokenizer
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---
license: apache-2.0
datasets: wikitext
license_link: https://llama.meta.com/llama3/license/
---
This is a quantized model of [Llama-3 70B Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) using GPTQ developed by [IST Austria](https://ist.ac.at/en/research/alistarh-group/)
using the following configuration:
- 4bit (8bit will follow)
- Act order: True
- Group size: 128
## Usage
Install **vLLM** and
run the [server](https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html#openai-compatible-server):
```
python -m vllm.entrypoints.openai.api_server --model cortecs/Meta-Llama-3-70B-Instruct-GPTQ
```
Access the model:
```
curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' {
"model": "cortecs/Meta-Llama-3-70B-Instruct-GPTQ",
"prompt": "San Francisco is a"
} '
```
## Evaluations
| __English__ | __Llama-3 70B Instruct__ | __Llama 3 70B Instruct GPTQ__ | __Mixtral Instruct__ |
|:--------------|:---------------------------|:--------------------------------|:-----------------------|
| Avg. | 76.19 | 75.14 | 73.17 |
| ARC | 71.6 | 70.7 | 71.0 |
| Hellaswag | 77.3 | 76.4 | 77.0 |
| MMLU | 79.66 | 78.33 | 71.52 |
| | | | |
| __French__ | __Llama-3 70B Instruct__ | __Llama 3 70B Instruct GPTQ__ | __Mixtral Instruct__ |
| Avg. | 70.97 | 70.27 | 68.7 |
| ARC_fr | 65.0 | 64.7 | 63.9 |
| Hellaswag_fr | 72.4 | 71.4 | 77.1 |
| MMLU_fr | 75.5 | 74.7 | 65.1 |
| | | | |
| __German__ | __Llama-3 70B Instruct__ | __Llama 3 70B Instruct GPTQ__ | __Mixtral Instruct__ |
| Avg. | 68.43 | 66.93 | 66.47 |
| ARC_de | 64.2 | 62.6 | 62.8 |
| Hellaswag_de | 67.8 | 66.7 | 72.1 |
| MMLU_de | 73.3 | 71.5 | 64.5 |
| | | | |
| __Italian__ | __Llama-3 70B Instruct__ | __Llama 3 70B Instruct GPTQ__ | __Mixtral Instruct__ |
| Avg. | 70.17 | 68.63 | 67.17 |
| ARC_it | 64.0 | 62.1 | 63.8 |
| Hellaswag_it | 72.6 | 71.0 | 75.6 |
| MMLU_it | 73.9 | 72.8 | 62.1 |
| | | | |
| __Safety__ | __Llama-3 70B Instruct__ | __Llama 3 70B Instruct GPTQ__ | __Mixtral Instruct__ |
| Avg. | 64.28 | 63.64 | 63.56 |
| RealToxicityPrompts | 97.9 | 98.1 | 93.2 |
| TruthfulQA | 61.91 | 59.91 | 64.61 |
| CrowS | 33.04 | 32.92 | 32.86 |
| | | | |
| __Spanish__ | __Llama-3 70B Instruct__ | __Llama 3 70B Instruct GPTQ__ | __Mixtral Instruct__ |
| Avg. | 72.5 | 71.3 | 68.8 |
| ARC_es | 66.7 | 65.7 | 64.4 |
| Hellaswag_es | 75.8 | 74 | 77.5 |
| MMLU_es | 75 | 74.2 | 64.6 |
Take with caution. We did not check for data contamination.
Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) using `limit=1000` for big datasets.
## Performance
| | requests/s | tokens/s |
|:--------------|-------------:|-----------:|
| NVIDIA L40Sx2 | 2 | 951.28 |