--- datasets: LeoLM/wikitext-en-de license: other license_link: https://llama.meta.com/llama3/license/ --- This is a quantized model of [Llama-3-SauerkrautLM-70b-Instruct](https://huggingface.co/VAGOSolutions/Llama-3-SauerkrautLM-70b-Instruct) 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/Llama-3-SauerkrautLM-70b-Instruct-GPTQ ``` Access the model: ``` curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' { "model": "cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ", "prompt": "San Francisco is a" } ' ``` ## Evaluations | __English__ | __[Llama-3-SauerkrautLM-70b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-70b-Instruct)__ | __[Llama-3-SauerkrautLM-70b-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ-8b)__ | __[Llama-3-SauerkrautLM-70b-Instruct-GPTQ](https://huggingface.co/cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ)__ | |:--------------|:------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------| | Avg. | 78.17 | 78.1 | 76.72 | | ARC | 74.5 | 74.4 | 73.0 | | Hellaswag | 79.2 | 79.2 | 78.0 | | MMLU | 80.8 | 80.7 | 79.15 | | | | | | | __German__ | __[Llama-3-SauerkrautLM-70b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-70b-Instruct)__ | __[Llama-3-SauerkrautLM-70b-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ-8b)__ | __[Llama-3-SauerkrautLM-70b-Instruct-GPTQ](https://huggingface.co/cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ)__ | | Avg. | 70.83 | 70.47 | 69.13 | | ARC_de | 66.7 | 66.2 | 65.9 | | Hellaswag_de | 70.8 | 71.0 | 68.8 | | MMLU_de | 75.0 | 74.2 | 72.7 | | | | | | | __Safety__ | __[Llama-3-SauerkrautLM-70b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-70b-Instruct)__ | __[Llama-3-SauerkrautLM-70b-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ-8b)__ | __[Llama-3-SauerkrautLM-70b-Instruct-GPTQ](https://huggingface.co/cortecs/Llama-3-SauerkrautLM-70b-Instruct-GPTQ)__ | | Avg. | 65.86 | 65.94 | 65.94 | | RealToxicityPrompts | 97.6 | 97.8 | 98.4 | | TruthfulQA | 67.07 | 66.92 | 65.56 | | CrowS | 32.92 | 33.09 | 33.87 | 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 L40Sx2 | 2.19 | 1044.76 | Performance measured on [cortecs inference](https://cortecs.ai).