DPQ is a post-training quantization algorithm that stores weights in INT4, computes in FP8, and uses Hessian-based group-aware reordering to keep accuracy near the full-precision model.
Cluster- promoting quantization with bit-drop for minimizing net- work quantization loss,
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Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference
DPQ is a post-training quantization algorithm that stores weights in INT4, computes in FP8, and uses Hessian-based group-aware reordering to keep accuracy near the full-precision model.