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Related Questions
- What is knowledge distillation in LLM fine-tuning and how does it differ from traditional fine-tuning?
- How does knowledge distillation improve the performance of LLMs in downstream tasks?
- What are the key challenges and limitations of knowledge distillation in LLM fine-tuning?
- Can you provide examples of applications where knowledge distillation has been successfully used in LLM fine-tuning?
- How does knowledge distillation impact the interpretability and explainability of LLMs?
- What are the potential risks and trade-offs associated with knowledge distillation in LLM fine-tuning?
- How can knowledge distillation be combined with other techniques, such as data augmentation and ensemble methods, to further improve LLM performance?
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