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Q22 Single choice

A company uses an AWS Lambda function to perform natural language processing (NLP) tasks. The company has attached a Lambda layer to the function. The Lambda layer contains scientific libraries that the function uses during processing.

The company added a large, pre-trained text-classification model to the Lambda layer. This addition increased the size of the Lambda layer to 8.7 GB. After the addition and a recent deployment, the Lambda function returned a RequestEntityTooLargeException error.

The company needs to update the Lambda function with a high-performing and portable solution to decrease the initialization time for the function.

Which solution will meet these requirements?

A
Store the large pre-trained model in an Amazon S3 bucket. Use the AWS SDK to access the model.
B
Create an Amazon EFS file system to store the large pre-trained model. Mount the file system to an Amazon EC2 instance. Configure the Lambda function to use the EFS file system.
C
Split the components of the Lambda layer into five new Lambda layers. Zip the new layers and attach them to the Lambda function. Update the function code to use the new layers.
D
Create a Docker container that includes the scientific libraries and the pre-trained model. Update the Lambda function to use the container image.

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