Core Concepts

What Are Zero-Shot and Few-Shot Learning?

Zero-shot learning is when a model performs a task it was not explicitly trained for, given only an instruction; few-shot learning is when a handful of examples are included in the prompt to guide it. Large language models are notably good at both, which is why careful prompting can adapt one model to many tasks.