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[Phi4-mini](https://huggingface.co/microsoft/Phi-4-mini-instruct) model quantized with [torchao](https://huggingface.co/docs/transformers/main/en/quantization/torchao) float8 dynamic activation and float8 weight quantization (per row granularity), by PyTorch team.
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# Quantization Recipe
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We used following code to get the quantized model:
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```
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[Phi4-mini](https://huggingface.co/microsoft/Phi-4-mini-instruct) model quantized with [torchao](https://huggingface.co/docs/transformers/main/en/quantization/torchao) float8 dynamic activation and float8 weight quantization (per row granularity), by PyTorch team.
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# Quantization Recipe
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Installation:
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```
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pip install transformers
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pip install --pre torchao --index-url https://download.pytorch.org/whl/nightly/cu126
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```
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We used following code to get the quantized model:
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```
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