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Editar Pregunta #366
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A company is evaluating customization options for a foundation model (FM). Match each data scenario to the appropriate customization technique. Drag and drop the correct customization technique next to the data scenario it describes.
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Fine-tuning uses labeled data (input-output pairs) to specialize a model for a specific task. Continued pre-training uses unlabeled data to extend a model's knowledge in a domain. Distillation transfers knowledge from a large teacher model to a smaller student model.
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