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CodeACT: Code Adaptive Compute-efficient Tuning Framework for Code LLMs

Published in arXiv (Cornell University) • Aug 5, 2024
NobleIDNI2P98W95R72S87
Authors:
Weijie Lv
,
Xuan Xia
,
Shengjun Huang

Abstract

Large language models (LLMs) have shown great potential in code-related tasks, yet open-source models lag behind their closed-source counterparts. To bridge this performance gap, existing methods generate vast amounts of synthetic data for fine-tuning, leading to inefficiencies in training. Motivate...

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