AIF-C01 Question 19

Community Discussion

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• Chose A1

  A is the correct answer.

• Chose A4

  Provide labeled data with the prompt field and the completion field: Fine-tuning a foundation model (FM) typically involves providing labeled data in the form of prompts (input) and completions (desired output). The model learns from this data to generate more accurate responses tailored to the company’s specific use case. This approach is aligned with how fine-tuning works, where the model adjusts its parameters based on the relationship between inputs (prompts) and outputs (completions).

• Chose A8

  Fine-tuning a foundation model involves providing labeled training data where each example consists of a prompt (the input to the model) and a completion (the desired output). This structure helps the model learn specific patterns or behaviors tailored to the company’s data and use case. In Amazon Bedrock, fine-tuning relies on a structured dataset that aligns with the model's learning requirements to improve its accuracy for domain-specific tasks.