A prompting method where models are shown a small number of examples to guide their outputs for new tasks.
More about Few-Shot Prompting
Few-Shot Prompting is a technique where an LLM is given a handful of example inputs and outputs within its prompt, helping it learn the desired pattern, style, or logic for a new task. Few-shot prompting is foundational for chain-of-thought reasoning, system prompts, and on-the-fly model adaptation.
It’s especially useful for zero-code configuration and when large amounts of training data aren’t available.
