Optimizing LLMs From a Dataset Perspective
Read OriginalThis technical article explores methods to optimize Large Language Models by carefully curating instruction datasets for fine-tuning. It covers supervised instruction fine-tuning, dataset composition, and practical applications for improving LLM efficiency and performance, with relevance to competitions like the NeurIPS LLM Efficiency Challenge.
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