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Fair-GPTQ: Bias-Aware Quantization for Large Language Models
The high memory demands of generative language models have drawn attention to quantization, which reduces memory usage by mapping model weights to lower-precision integers. However, recent empirical studies show that, while efficient, quantization can increase the likelihood of generating biased out
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