GLOSSARY > FEW-SHOT LEARNING
Few-Shot Learning
The practice of feeding a machine learning model with a very small amount of training data to adapt it to a specific task.
Few-Shot Learning leverages the vast pre-trained knowledge of a Foundation Model. By providing just three or four highly accurate examples within the prompt (Prompt Engineering), the model instantly grasps the desired pattern and format, bypassing the need for expensive, full-scale fine-tuning.
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