MiniPLM: Knowledge Distillation for Pre-Training Language Models
MiniPLM: Knowledge Distillation for Pre-Training Language Models
Knowledge distillation (KD) is widely used to train small, high-performing student language models (LMs) using large teacher LMs. While effective in fine-tuning, KD during pre-training faces challenges in efficiency, flexibility, and effectiveness. Existing methods either incur high computational costs due to online teacher inference, require tokenization matching between teacher and …