Crucial Exams

AWS Certified AI Practitioner AIF-C01 Practice Question

A company needs to specialize a publicly available foundation model so it understands the company's industry-specific jargon. To minimize GPU cost, it wants to update only a small fraction of the model's parameters instead of retraining the entire network. Which fine-tuning method best meets these requirements?

  • Continuous pre-training on a large, new corpus

  • Parameter-efficient fine-tuning (for example, LoRA adapters)

  • Training a completely new model from scratch

  • Zero-shot prompting with the base model

AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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