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KDFlow: A User-Friendly and Efficient Knowledge Distillation Framework for Large Language Models
Knowledge distillation (KD) is widely used to compress and post-train large language models (LLMs), yet many existing frameworks execute teacher inference with the same training-oriented backend as student optimization, leading to suboptimal efficiency. In this paper, we propose KDFlow, a novel fram
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