Oct 30, 2024 · To address this problem, we propose gradient-aware weight quantization (GWQ), the first quantization approach for low-bit weight quantization that leverages gradients to …

GWQ is the first accurate first-order gradient-aware post-training weight quantization method for pre-trained LLMs, requiring only a minimal quantity of calibration data to identify outliers …

To address this problem, we propose gradient-aware weight quantization (GWQ), the first quantization approach for low- bit weight quantization that leverages gradients to localize …

加权量化和（WQS）回归是一种统计 模型，用于环境暴露、表观/基因组学和代谢组学研究等常见的高维数据集的多变量回归。 该模型构建了一个加权指数，估计所有预测变量对结果的混合 …

Oct 30, 2024 · To address this problem, we propose gradient-aware weight quantization (GWQ), the first quantization approach for low-bit weight quantization that leverages gradients to …

In this paper, we propose a Group-Wise Quantization framework, called GWQ, to reduce computational consumption during the activation data pass process by allowing multiple layers …

In this paper, we propose a Group-Wise Quantization framework, called GWQ, to reduce computational consumption during the activation data pass process by allowing multiple layers …

Oct 30, 2024 · To address this problem, we propose gradient-aware weight quantization (GWQ), the first quantization approach for low-bit weight quantization that leverages gradients to...

Dec 27, 2024 · 为了解决这个问题，我们提出了梯度感知权重量化（GWQ），这是第一个低位权重量化的量化方法，它利用梯度来定位异常值，只需要最少量的校准数据即可进行 异常值检测 …

To address this problem, we propose gradient-aware weight quantization (GWQ), the first quantization approach for low-bit weight quantization that leverages gradients to localize …