MLA-C01 · Question #89
MLA-C01 Question #89: Real Exam Question with Answer & Explanation
Sign in or unlock MLA-C01 to reveal the answer and full explanation for question #89. The question stem and answer options stay visible for context.
Question
A company needs to use Retrieval Augmented Generation (RAG) to supplement an open source large language model (LLM) that runs on Amazon Bedrock. The company's data for RAG is a set of documents in an Amazon S3 bucket. The documents consist of .csv files and .docx files. Which solution will meet these requirements with the LEAST operational overhead?
Options
- ACreate a pipeline in Amazon SageMaker Pipelines to generate a new model. Call the new model
- BConvert the data into vectors. Store the data in an Amazon Neptune database. Connect the
- CFine-tune an existing LLM by using an AutoML job in Amazon SageMaker. Configure the S3
- DCreate a knowledge base for Amazon Bedrock. Configure a data source that references the S3
Unlock MLA-C01 to see the answer
You've previewed enough free MLA-C01 questions. Unlock MLA-C01 for full answers, explanations, the timed quiz mode, progress tracking, and the master PDF. Question stem and options stay visible so you can still see what's on the exam.