AI Training
Few-shot Learning
Teaching an AI model new tasks by providing just a few examples in the prompt.
Few-shot learning is a technique where an AI model learns to perform a task from just a few examples provided in the prompt. Instead of fine-tuning on thousands of examples, you include 2-5 demonstrations of the desired input-output pattern. The model generalizes from these examples to handle new inputs. Few-shot prompting is more reliable than zero-shot for complex tasks and more practical than fine-tuning when data is limited or tasks change frequently.
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