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--- |
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license: other |
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datasets: wikitext |
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license_link: https://llama.meta.com/llama3/license/ |
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--- |
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This is a quantized model of [Meta-Llama-3-70B-Instruct.yaml](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct.yaml) 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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- 4bit |
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- Act order: True |
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- Group size: 128 |
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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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python -m vllm.entrypoints.openai.api_server --model cortecs/Meta-Llama-3-70B-Instruct-GPTQ |
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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/Meta-Llama-3-70B-Instruct-GPTQ", |
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"prompt": "San Francisco is a" |
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} ' |
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``` |
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## Evaluations |
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| __English__ | __[Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)__ | __[Meta-Llama-3-70B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-70B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ)__ | |
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|:--------------|:-----------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------| |
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| Avg. | 76.19 | 76.16 | 75.14 | |
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| ARC | 71.6 | 71.4 | 70.7 | |
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| Hellaswag | 77.3 | 77.1 | 76.4 | |
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| MMLU | 79.66 | 79.98 | 78.33 | |
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| __French__ | __[Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)__ | __[Meta-Llama-3-70B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-70B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ)__ | |
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| Avg. | 70.97 | 71.03 | 70.27 | |
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| ARC_fr | 65.0 | 65.3 | 64.7 | |
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| Hellaswag_fr | 72.4 | 72.4 | 71.4 | |
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| MMLU_fr | 75.5 | 75.4 | 74.7 | |
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| __German__ | __[Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)__ | __[Meta-Llama-3-70B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-70B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ)__ | |
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| Avg. | 68.43 | 68.37 | 66.93 | |
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| ARC_de | 64.2 | 64.3 | 62.6 | |
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| Hellaswag_de | 67.8 | 67.7 | 66.7 | |
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| MMLU_de | 73.3 | 73.1 | 71.5 | |
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| | | | | |
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| __Italian__ | __[Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)__ | __[Meta-Llama-3-70B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-70B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ)__ | |
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| Avg. | 70.17 | 70.43 | 68.63 | |
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| ARC_it | 64.0 | 64.3 | 62.1 | |
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| Hellaswag_it | 72.6 | 72.4 | 71.0 | |
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| MMLU_it | 73.9 | 74.6 | 72.8 | |
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| __Safety__ | __[Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)__ | __[Meta-Llama-3-70B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-70B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ)__ | |
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| Avg. | 64.28 | 64.17 | 63.64 | |
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| RealToxicityPrompts | 97.9 | 97.8 | 98.1 | |
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| TruthfulQA | 61.91 | 61.67 | 59.91 | |
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| CrowS | 33.04 | 33.04 | 32.92 | |
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| __Spanish__ | __[Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct)__ | __[Meta-Llama-3-70B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-70B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ)__ | |
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| Avg. | 72.5 | 72.7 | 71.3 | |
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| ARC_es | 66.7 | 66.9 | 65.7 | |
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| Hellaswag_es | 75.8 | 75.9 | 74 | |
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| MMLU_es | 75 | 75.3 | 74.2 | |
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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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## Performance |
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| | requests/s | tokens/s | |
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|:--------------|-------------:|-----------:| |
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| NVIDIA L40Sx2 | 2 | 951.28 | |
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Performance measured on [cortecs inference](https://cortecs.ai). |
