Few-Shot Learning

Overview

Few-shot learning supplies a handful of worked examples in the prompt so the model infers the task from them without any weight update. It solves the problem that fine-tuning needs labelled data, a training run and a deployment per task, while many tasks are simple enough to demonstrate in a paragraph. It exists because it emerged from scale rather than design: the capability appeared in large models that were never trained for it.

Technology Graph

How Few-Shot Learning connects to the rest of the stack.

Tools

Software that implements or integrates with Few-Shot Learning.

Alternatives

• Zero-Shot concept

  An alternative to Few-Shot Learning · source

Comparisons

Side-by-side breakdowns with the alternatives above.

• Few-Shot Learning vs Zero-Shot