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The Post-Training Quantization Of Frantar

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Frantar et al. (2022) introduced a data-driven post-training quantization method using approximate second-order information, reducing GPT-family models to 4 bits with small quality drop. Name it (four-letter acronym). Flag format: CONGRESS{acronym}. Example: CONGRESS{awq}.
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The model family + 'quantization'.

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