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Co-authored-by: Abhinav Agarwalla <abhinavnmagic@users.noreply.huggingface.co>

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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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+
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+ # Meta-Llama-3-70B-Instruct-FP8
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+
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+ ## Model Overview
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+ Meta-Llama-3-70B-Instruct quantized to FP8 weights and activations using per-tensor quantization, ready for inference with vLLM >= 0.5.0.
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+
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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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+
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+ ## Evaluation
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+
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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 | 72.69 | 72.61 |
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+ | hellaswag<br>10-shot | 85.50 | 85.41 |
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+ | mmlu<br>5-shot | 80.18 | 80.06 |
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+ | truthfulqa<br>0-shot | 62.90 | 62.73 |
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+ | winogrande<br>5-shot | 83.34 | 83.03 |
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+ | gsm8k<br>5-shot | 92.49 | 91.12 |
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+ | **Average<br>Accuracy** | **79.51** | **79.16** |
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+ | **Recovery** | **100%** | **99.55%** |
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+