An effective approach to address this issue is model quantization, which achieves network compression and inference speedup by reducing the parameters bit-width during inference. Mixed-precision ...

Gapless surface states within a bulk energy gap are considered irrefutable proof of TI. Topological surface states (TSS) also exist in Weyl semimetals (WSMs), characterized by the presence of ...

Their large memory footprint and high computational cost hinder efficient deployment. Post-Training Quantization (PTQ) is a promising technique to alleviate this issue and accelerate LLM inference.

Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...

HQQ is a fast and accurate model quantizer that skips the need for calibration data. Quantize the largest models, without calibration data, in just a few minutes at most 🚀.