Zhihua Ban

GAP: a Global Adaptive Pruning Method for Large Language Models

The deployment of Large Language Models (LLMs) faces significant challenges due to high computational costs,driving the demand for effective pruning techniques. Existing structured pruning methods employ uniform compression rates across network layers, neglecting the varying importance of different