Amazon
AIF-C01 · Question #38
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. Which strategy will…
The correct answer is A. Provide labeled data with the prompt field and the completion field. Providing labeled data with both a prompt field and a completion field is the correct strategy for fine-tuning a foundation model (FM) on Amazon Bedrock.
Submitted by haruto_sh· Mar 30, 2026Applications of Foundation Models
Question
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. Which strategy will successfully fine-tune the model?
Options
- AProvide labeled data with the prompt field and the completion field.
- BPrepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
- CPurchase Provisioned Throughput for Amazon Bedrock.
- DTrain the model on journals and textbooks.
How the community answered
(23 responses)- A83% (19)
- B4% (1)
- C9% (2)
- D4% (1)
Explanation
Providing labeled data with both a prompt field and a completion field is the correct strategy for fine-tuning a foundation model (FM) on Amazon Bedrock.
Topics
#fine-tuning#Amazon Bedrock#labeled data#foundation models
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