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Meta-Llama-3-8B-Instruct-GPTQ-8b

Text Generation
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llama
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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  ---
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+ datasets: wikitext
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+ license: other
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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-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) 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/Meta-Llama-3-8B-Instruct-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/Meta-Llama-3-8B-Instruct-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__ | __[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)__ | __[Meta-Llama-3-8B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-8B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ)__ |
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+ |:--------------|:---------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------|
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+ | Avg. | 66.97 | 67.0 | 63.52 |
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+ | ARC | 62.5 | 62.5 | 54.6 |
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+ | Hellaswag | 70.3 | 70.3 | 69.5 |
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+ | MMLU | 68.11 | 68.21 | 66.46 |
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+ | | | | |
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+ | __French__ | __[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)__ | __[Meta-Llama-3-8B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-8B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ)__ |
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+ | Avg. | 57.73 | 57.7 | 53.33 |
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+ | Hellaswag_fr | 61.7 | 62.2 | 59.3 |
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+ | ARC_fr | 53.3 | 53.1 | 46.4 |
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+ | MMLU_fr | 58.2 | 57.8 | 54.3 |
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+ | | | | |
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+ | __German__ | __[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)__ | __[Meta-Llama-3-8B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-8B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ)__ |
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+ | Avg. | 53.47 | 53.67 | 49.0 |
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+ | ARC_de | 49.1 | 49.0 | 41.6 |
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+ | Hellaswag_de | 55.0 | 55.2 | 53.3 |
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+ | MMLU_de | 56.3 | 56.8 | 52.1 |
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+ | | | | |
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+ | __Italian__ | __[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)__ | __[Meta-Llama-3-8B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-8B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ)__ |
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+ | Avg. | 56.73 | 56.67 | 51.3 |
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+ | Hellaswag_it | 61.3 | 61.3 | 58.4 |
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+ | MMLU_it | 57.3 | 57.0 | 53.0 |
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+ | ARC_it | 51.6 | 51.7 | 42.5 |
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+ | | | | |
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+ | __Safety__ | __[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)__ | __[Meta-Llama-3-8B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-8B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ)__ |
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+ | Avg. | 61.42 | 61.42 | 61.53 |
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+ | RealToxicityPrompts | 97.2 | 97.2 | 97.2 |
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+ | TruthfulQA | 51.65 | 51.58 | 51.98 |
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+ | CrowS | 35.42 | 35.48 | 35.42 |
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+ | | | | |
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+ | __Spanish__ | __[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)__ | __[Meta-Llama-3-8B-Instruct-GPTQ-8b](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b)__ | __[Meta-Llama-3-8B-Instruct-GPTQ](https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ)__ |
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+ | Avg. | 59 | 58.63 | 54.6 |
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+ | ARC_es | 54.1 | 53.8 | 46.9 |
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+ | Hellaswag_es | 63.8 | 63.3 | 60.3 |
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+ | MMLU_es | 59.1 | 58.8 | 56.6 |
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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 | 2.75 | 1312.26 |
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+ | NVIDIA L4x2 | 4.36 | 2080.17 |
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+ | NVIDIA L4x4 | 5.33 | 2539.76 |
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+ Performance measured on [cortecs inference](https://cortecs.ai).