cortecs
/

Llama-3-SauerkrautLM-70b-Instruct-GPTQ

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 ---
+datasets: LeoLM/wikitext-en-de
+license: apache-2.0
+license_link: https://llama.meta.com/llama3/license/
 ---
+This is a quantized model of [SKLM Llama-3 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 (8bit will follow)
+- 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__   | __SKLM Llama-3 70B Instruct__   | __SKLM Llama-3 70B Instruct GPTQ__   | __SKLM Mixtral Instruct__   |
+|:--------------|:--------------------------------|:-------------------------------------|:----------------------------|
+| Avg.          | 78.17                           | 76.72                                | 73.47                       |
+| ARC           | 74.5                            | 73.0                                 | 71.7                        |
+| Hellaswag     | 79.2                            | 78.0                                 | 77.4                        |
+| MMLU          | 80.8                            | 79.15                                | 71.31                       |
+|               |                                 |                                      |                             |
+| __German__   | __SKLM Llama-3 70B Instruct__   | __SKLM Llama-3 70B Instruct GPTQ__   | __SKLM Mixtral Instruct__   |
+| Avg.         | 70.83                           | 69.13                                | 66.43                       |
+| ARC_de       | 66.7                            | 65.9                                 | 62.7                        |
+| Hellaswag_de | 70.8                            | 68.8                                 | 72.9                        |
+| MMLU_de      | 75.0                            | 72.7                                 | 63.7                        |
+|              |                                 |                                      |                             |
+| __Safety__          |   __SKLM Llama-3 70B Instruct__ |   __SKLM Llama-3 70B Instruct GPTQ__ |   __SKLM Mixtral Instruct__ |
+| Avg.                |                           65.86 |                                65.94 |                       64.18 |
+| RealToxicityPrompts |                           97.6  |                                98.4  |                       93.2  |
+| TruthfulQA          |                           67.07 |                                65.56 |                       65.84 |
+| CrowS               |                           32.92 |                                33.87 |                       33.51 |
+Take with caution. We did not check for data contamination.
+     Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) using `limit=1000` for big datasets.
+## Performance
+|               |   requests/s |   tokens/s |
+|:--------------|-------------:|-----------:|
+| NVIDIA L40Sx2 |         2.19 |    1044.76 |