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README.md
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---
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tags:
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- fp8
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- vllm
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---
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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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