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tags: |
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- fp8 |
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- vllm |
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# Mixtral-8x22B-Instruct-v0.1-FP8 |
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## Model Overview |
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Mixtral-8x22B-Instruct-v0.1 quantized to FP8 weights and activations using per-tensor quantization, ready for inference with vLLM >= 0.5.0. |
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## Usage and Creation |
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Produced using [AutoFP8 with calibration samples from ultrachat](https://github.com/neuralmagic/AutoFP8/blob/147fa4d9e1a90ef8a93f96fc7d9c33056ddc017a/example_dataset.py). |
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## Evaluation |
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### Open LLM Leaderboard evaluation scores |
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| | Meta-Llama-3-70B-Instruct | Meta-Llama-3-70B-Instruct-FP8<br>(this model) | |
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| :------------------: | :----------------------: | :------------------------------------------------: | |
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| arc-c<br>25-shot | 71.58 | 72.09 | |
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| hellaswag<br>10-shot | 86.94 | 86.83 | |
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| mmlu<br>5-shot | 83.97 | 84.06 | |
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| truthfulqa<br>0-shot | 66.98 | 66.95 | |
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| winogrande<br>5-shot | 82.79 | 83.18 | |
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| gsm8k<br>5-shot | 87.56 | 88.93 | |
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| **Average<br>Accuracy** | **79.97** | **80.34** | |
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| **Recovery** | **100%** | **100.46%** | |
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