AIBullisharXiv – CS AI · Mar 37/105
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KDFlow: A User-Friendly and Efficient Knowledge Distillation Framework for Large Language Models
Researchers have developed KDFlow, a new framework for compressing large language models that achieves 1.44x to 6.36x faster training speeds compared to existing knowledge distillation methods. The framework uses a decoupled architecture that optimizes both training and inference efficiency while reducing communication costs through innovative data transfer techniques.