Layer-wise Curriculum Learning for Efficient LLM Compression
A novel strategy for streamlining knowledge transfer to make massive language models more efficient and compact.
In this paper, we introduce layer-wise curriculum learning for efficient LLM compression. The proposed method facilitates the knowledge transfer from the teacher model to the student model, utilizing a curriculum learning approach that begins with easier optimization tasks and pr...
ArXiv CS.LG
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Layer-wise curriculum learning addresses the computational bottleneck of compressing massive models by strategically easing the difficulty of the optimization process. This incremental approach improves both the efficiency of knowledge distillation and the performance retention of the resulting lightweight LLMs.
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