Q84 — AWS AIF-C01 Ch.1

Question 84 of 100 | ← Chapter 1

A company is using Amazon Bedrock foundation models for internal document summarization use cases. The company has trained a custom model to improve summarization quality. What action must the company take to use the custom model via Amazon Bedrock?

• A. Purchase provisioned throughput for the custom model.
• B. Deploy the custom model in an Amazon SageMaker endpoint to enable real-time inference. ✓
• C. Register the model in the Amazon SageMaker Model Registry.
• D. Grant permissions to access the custom model in Amazon Bedrock.

Correct Answer: B. Deploy the custom model in an Amazon SageMaker endpoint to enable real-time inference.

Explanation

To use a custom model via Amazon Bedrock, real-time inference capability is essential. Amazon SageMaker provides endpoint deployment functionality, allowing users to deploy trained models in the cloud for real-time inference. This step is critical to integrate the custom model effectively with Amazon Bedrock and enhance document summarization quality. Therefore, the company must deploy the custom model in an Amazon SageMaker endpoint.