What is the difference between pretraining and fine-tuning?
LLM Engineer Interview Questions: Transformer Architecture, Self-Attention, and Modern LLM Foundations
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What is the difference between pretraining and fine-tuning?
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Pretraining is the initial training of a language model on a massive corpus of unlabeled text using self-supervised objectives like next-token prediction. Fine-tuning takes a pretrained model and adapts it to a specific task, domain, or instruction-following style using a smaller labeled dataset. Pretraining costs millions of dollars; fine-tuning is typically much cheaper.
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