OmniQuant

OmniQuant is a lightweight, differentiable PTQ algorithm for LLMs. Its core mechanism consists of structural transformation and learnable channel scaling. On top of learnable clipping, it introduces channel-scaling structural transformations to boost the accuracy of low-bit W/A quantization. For details about the algorithm, see OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.