--- 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: - 4bit - 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-4b ``` Access the model: ``` curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' { "model": "cortecs/Mistral-7B-Instruct-v0.3-GPTQ-4b", "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 | 3.75 | 1867.13 | | NVIDIA L4x2 | 5.03 | 2503.83 | | NVIDIA L4x4 | 5.86 | 2916.3 | Performance measured on [cortecs inference](https://cortecs.ai).