An empirical study of LLaMA3 quantization: from LLMs to MLLMs

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language models (MLLMs), widely used in computer vision and natural...

Full description

Saved in:
Bibliographic Details
Main Authors: Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno
Format: Article
Language:English
Published: Springer 2024-12-01
Series:Visual Intelligence
Subjects:
Model quantization
Large language model
Multi-modal
Deep learning
Online Access:https://doi.org/10.1007/s44267-024-00070-x
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1007/s44267-024-00070-x

Similar Items