Few-Shot Learning

Teaching a model a task using only a small number of examples.

Few-shot learning provides a model with a limited set of demonstrations before asking it to complete a similar task. Each example shows the expected relationship between input and output.

It is useful when task instructions are difficult to express precisely. Carefully selected examples can improve formatting, tone, classification accuracy and reasoning behaviour.

Also in

Diffusion Models Small Language Models Retrieval-Augmented Generation Prompt Engineering Context Engineering Supervised Fine-Tuning

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