Zero-Shot

Resumen

Zero-shot means asking a model to do something it was not trained on and giving it no examples - only a description of the task. It solves the problem that every supervised approach needs labelled data for each new task, which does not scale to tasks nobody has collected data for. It exists as the capability that made general-purpose models useful, and as the upper bound that few-shot prompting is measured against.

Grafo de tecnologías

Cómo se conecta Zero-Shot con el resto del stack.

Alternativas

• Few-Shot Learning technique

  Una alternativa a Zero-Shot · source

Comparativas

Comparativas detalladas con las alternativas anteriores.

• Few-Shot Learning vs Zero-Shot