2024
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models
EMNLP 2024main
Scaling model size significantly challenges the deployment and inference of Large Language Models (LLMs). Due to the redundancy in LLM weights, recent research has focused on pushing weight-only quantization to extremely low-bit (even down to 2 bits). It reduces memory requirements, optimizes storag…