科研项目
Resource Efficient LLM Fine-tuning and Serving
摘要
Large Language Models (LLMs) have achieved great success in many real-world applications. However, fine-tuning and serving LLMs require much memory and computing resources. This project aims to develop cutting-edge techniques to improve the resource efficiency of LLM fine-tuning and serving.
项目成员
文泽忆
助理教授
项目周期
2023-Present
研究领域
Data-driven AI & Machine Learning、High-Performance Systems for Data Analytics
关键词
Efficiency, Fine-tuning, Large Language Models, Model Serving