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AIF-C01 practice question: Training and fine-tuning (3 of 4)

Applications of Foundation Models A free question from our original AIF-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.

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A retailer uses a very large foundation model to classify customer emails. Accuracy is excellent, but responses are slow and costly at peak volume.

The retailer has 10,000 past emails but no labeled answers, and it wants a model that keeps similar accuracy for this one task at lower cost.

Which approach fits BEST?

Choose one answer.

  1. A. Continued pre-training of the large model on all of the company's historical emails
  2. B. Raising the large model's temperature so it produces shorter answers
  3. C. Pre-training a new small model from scratch on public email datasets
  4. D. Model distillation, where the large model's answers train a smaller student
Show the answer and explanation

Answer: D

  • A. Wrong: Continued pre-training adds knowledge to the same large model, which stays just as slow and costly per request. It also needs large volumes of unlabeled text, not a task-specific target.
  • B. Wrong: Temperature changes randomness in the output, not the speed or cost of running the model. Shorter answers would not make a classification task cheaper.
  • C. Wrong: Training from scratch is the most expensive route and needs a very large dataset. A model trained on public email data would not match the retailer's accuracy on its own emails.
  • D. Right: Correct. Amazon Bedrock Model Distillation takes prompts, lets the teacher model generate responses, and fine-tunes a smaller, cheaper student on them. The retailer's emails can serve as prompts, so no labeled answers are needed. Learn more: Amazon Bedrock Model Distillation (opens in a new tab)

Explanation

Amazon Bedrock Model Distillation transfers knowledge from a large teacher model to a smaller student model that is faster and cheaper to run. It can start from prompts alone, because the teacher generates the responses. The resulting distilled model is available only to the customer.

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