Few-shot prompt refers to a method where the AI model is given a small number of examples (usually less than 10) during the inference stage to understand and generate similar content. This approach helps the model to quickly adapt to new tasks, reducing the need for extensive training data. It's a technique commonly used in Natural Language Processing and Machine Learning models to improve their performance and versatility.
See also "Zero-shot Prompt" and "One-shot Prompt".
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