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

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  - vllm
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  ---
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- # Qwen2-72B-Instruct-FP8
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- Ready to use with `vllm>=0.5.0`.
 
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- Quantized with [AutoFP8](https://github.com/neuralmagic/autofp8) using the following script on 8xA100:
 
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  ```python
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  from datasets import load_dataset
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  )
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  model.quantize(examples)
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  model.save_quantized(quantized_model_dir)
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - vllm
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+ # Qwen2-72B-Instruct-FP8
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+ ## Model Overview
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+ Qwen2-72B-Instruct 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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  ```python
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  from datasets import load_dataset
 
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  )
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  model.quantize(examples)
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  model.save_quantized(quantized_model_dir)
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+ ```
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+
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+ ## Evaluation
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+ ### Open LLM Leaderboard evaluation scores
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+ | | Qwen2-72B-Instruct | Qwen2-72B-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 | xx.xx | 84.06 |
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+ | truthfulqa<br>0-shot | 66.94 | 66.95 |
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+ | winogrande<br>5-shot | 82.79 | 83.18 |
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+ | gsm8k<br>5-shot | xx.xx | 88.93 |
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+ | **Average<br>Accuracy** | **xx.xx** | **80.34** |
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+ | **Recovery** | **100%** | **xx.xx%** |
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+