What is Few-Shot Prompting?
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.
Frequently Asked Questions
How is few-shot prompting different from fine-tuning?
Few-shot prompting adapts behavior at inference time with prompt examples, while fine-tuning requires model retraining.
What types of tasks benefit from few-shot prompting?
Tasks like code generation, dialogue, math problems, and language translation.
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