Eugene Yan • 2/11/2024

How to Generate and Use Synthetic Data for Finetuning

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This technical article details the use of synthetic data for fine-tuning large language models (LLMs). It compares two primary generation methods—distillation from stronger models and self-improvement from a model's own outputs—and explains their application in pretraining, instruction-tuning, and preference-tuning to enhance model performance, generalization, and efficiency while addressing privacy and copyright concerns.

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#llm #Finetuning #Instruction Tuning
How to Generate and Use Synthetic Data for Finetuning

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