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---
datasets: wikitext
---
This is a quantized model of [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) using GPTQ developed by [IST Austria](https://ist.ac.at/en/research/alistarh-group/)
using the following configuration:
- 8bit
- 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/Mistral-7B-Instruct-v0.3-GPTQ-8b
```
Access the model:
```
curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' {
"model": "cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b",
"prompt": "San Francisco is a"
} '
```
## Evaluations
| __English__ | __[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-8b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-4b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b)__ |
|:--------------|:--------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|
| Avg. | 67.65 | 67.72 | 66.95 |
| ARC | 64.2 | 64.1 | 62.1 |
| Hellaswag | 75.6 | 75.6 | 76.0 |
| MMLU | 63.16 | 63.47 | 62.75 |
| | | | |
| __French__ | __[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-8b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-4b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b)__ |
| Avg. | 56.4 | 56.17 | 54.77 |
| ARC_fr | 51.9 | 51.4 | 50.0 |
| Hellaswag_fr | 65.8 | 65.8 | 63.8 |
| MMLU_fr | 51.5 | 51.3 | 50.5 |
| | | | |
| __German__ | __[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-8b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-4b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b)__ |
| Avg. | 51.83 | 51.73 | 51.7 |
| ARC_de | 47.6 | 47.5 | 47.3 |
| Hellaswag_de | 58.9 | 59.0 | 57.3 |
| MMLU_de | 49.0 | 48.7 | 50.5 |
| | | | |
| __Italian__ | __[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-8b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-4b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b)__ |
| Avg. | 54.93 | 54.8 | 52.83 |
| ARC_it | 51.6 | 51.6 | 49.3 |
| Hellaswag_it | 63.5 | 63.8 | 61.0 |
| MMLU_it | 49.7 | 49.0 | 48.2 |
| | | | |
| __Safety__ | __[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-8b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-4b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b)__ |
| Avg. | 60.32 | 60.54 | 64.8 |
| RealToxicityPrompts | 89.7 | 90.0 | 90.7 |
| TruthfulQA | 59.71 | 59.48 | 58.32 |
| CrowS | 31.54 | 32.14 | 45.38 |
| | | | |
| __Spanish__ | __[Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-8b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b)__ | __[Mistral-7B-Instruct-v0.3-GPTQ-4b](https://huggingface.co/cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b)__ |
| Avg. | 57.9 | 57.97 | 56.1 |
| ARC_es | 53.5 | 53.5 | 51 |
| Hellaswag_es | 68.5 | 68.5 | 66.2 |
| MMLU_es | 51.7 | 51.9 | 51.1 |
We did not check for data contamination.
Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) using `limit=1000`.
## Performance
| | requests/s | tokens/s |
|:------------|-------------:|-----------:|
| NVIDIA L4x1 | 2.63 | 1308.8 |
| NVIDIA L4x2 | 4.36 | 2168.56 |
| NVIDIA L4x4 | 5.53 | 2751.53 |
Performance measured on [cortecs inference](https://cortecs.ai). |