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Mistral-7B-Instruct-v0.3-GPTQ-8b

Text Generation
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mistral
conversational
Inference Endpoints
8-bit precision
gptq
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- library_name: transformers
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- # Model Card for Model ID
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+ datasets: wikitext
 
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  ---
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+ 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/)
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+ using the following configuration:
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+ - 8bit
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+ - Act order: True
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+ - Group size: 128
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+
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+ ## Usage
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+ Install **vLLM** and
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+ run the [server](https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html#openai-compatible-server):
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+
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+ ```
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+ python -m vllm.entrypoints.openai.api_server --model cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b
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+ ```
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+ Access the model:
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+ ```
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+ curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' {
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+ "model": "cortecs/Mistral-7B-Instruct-v0.3-GPTQ-8b",
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+ "prompt": "San Francisco is a"
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+ } '
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+ ```
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+
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+ ## Evaluations
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+ | __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)__ |
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+ |:--------------|:--------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|
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+ | Avg. | 67.65 | 67.72 | 66.95 |
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+ | ARC | 64.2 | 64.1 | 62.1 |
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+ | Hellaswag | 75.6 | 75.6 | 76.0 |
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+ | MMLU | 63.16 | 63.47 | 62.75 |
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+ | | | | |
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+ | __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)__ |
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+ | Avg. | 56.4 | 56.17 | 54.77 |
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+ | ARC_fr | 51.9 | 51.4 | 50.0 |
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+ | Hellaswag_fr | 65.8 | 65.8 | 63.8 |
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+ | MMLU_fr | 51.5 | 51.3 | 50.5 |
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+ | | | | |
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+ | __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)__ |
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+ | Avg. | 51.83 | 51.73 | 51.7 |
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+ | ARC_de | 47.6 | 47.5 | 47.3 |
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+ | Hellaswag_de | 58.9 | 59.0 | 57.3 |
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+ | MMLU_de | 49.0 | 48.7 | 50.5 |
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+ | | | | |
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+ | __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)__ |
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+ | Avg. | 54.93 | 54.8 | 52.83 |
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+ | ARC_it | 51.6 | 51.6 | 49.3 |
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+ | Hellaswag_it | 63.5 | 63.8 | 61.0 |
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+ | MMLU_it | 49.7 | 49.0 | 48.2 |
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+ | | | | |
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+ | __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)__ |
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+ | Avg. | 60.32 | 60.54 | 64.8 |
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+ | RealToxicityPrompts | 89.7 | 90.0 | 90.7 |
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+ | TruthfulQA | 59.71 | 59.48 | 58.32 |
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+ | CrowS | 31.54 | 32.14 | 45.38 |
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+ | | | | |
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+ | __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)__ |
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+ | Avg. | 57.9 | 57.97 | 56.1 |
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+ | ARC_es | 53.5 | 53.5 | 51 |
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+ | Hellaswag_es | 68.5 | 68.5 | 66.2 |
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+ | MMLU_es | 51.7 | 51.9 | 51.1 |
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+
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+ We did not check for data contamination.
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+ Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) using `limit=1000`.
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+
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+ ## Performance
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+ | | requests/s | tokens/s |
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+ |:------------|-------------:|-----------:|
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+ | NVIDIA L4x1 | 2.63 | 1308.8 |
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+ | NVIDIA L4x2 | 4.36 | 2168.56 |
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+ | NVIDIA L4x4 | 5.53 | 2751.53 |
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+ Performance measured on [cortecs inference](https://cortecs.ai).