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Fine-tuning

Continue training a pre-trained model on task-specific data to adapt its behaviour.

technique Techniques 18 relationships

Overview

Fine-tuning continues training an already pre-trained model on a smaller, task-specific dataset so that its weights shift toward the behaviour you want. It solves the problem that a general model may not follow a house style, a domain vocabulary or a fixed output format. It exists because pre-training is expensive but adaptation is not: starting from a pre-trained checkpoint means a modest dataset is enough. It is the main alternative to retrieval when the goal is behaviour rather than fresh facts.

Technology Graph

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Alternatives

  • RAG technique

    An alternative to Fine-tuning · source

Comparisons

Side-by-side breakdowns with the alternatives above.