3 citations · 5 across the 5 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.CL2023★ 1 cited
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks
Xiaoxia Wu, Haojun Xia, Stephen Youn +9
This study examines 4-bit quantization methods like GPTQ in large language models (LLMs), highlighting GPTQ's overfitting and limited enhancement in Zero-Shot tasks. While prior wo…
cs.DC2023★ 1 cited
Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity
Haojun Xia, Zhen Zheng, Yuchao Li +6
With the fast growth of parameter size, it becomes increasingly challenging to deploy large generative models as they typically require large GPU memory consumption and massive com…