2 papers
cs.AI2024
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs
Hanlin Tang, Yifu Sun, Decheng Wu +3
Large language models (LLMs) have proven to be very superior to conventional methods in various tasks. However, their expensive computations and high memory requirements are prohib…
cs.LG2023
E-Sparse: Boosting the Large Language Model Inference through Entropy-based N:M Sparsity
Yun Li, Lin Niu, Xipeng Zhang +3
Traditional pruning methods are known to be challenging to work in Large Language Models (LLMs) for Generative AI because of their unaffordable training process and large computati…