[Jun 27, 2026] HP HPE2-B08 Exam Dumps Files, Q7/31: An enterprise architecture team is debating the best method to adapt a general-purpose Large Language

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Question 7/31

An enterprise architecture team is debating the best method to adapt a general-purpose Large Language Model (LLM) for two different, highly-specialized internal use cases:
1. Use Case A: A customer support chatbot that must provide answers strictly based on a rapidly changing knowledge base of product manuals and technical notes. Verifiability and traceability of the information source are critical.
2. Use Case B: An internal code generation assistant that needs to learn the company's specific coding style, proprietary frameworks, and API usage patterns from a large, static codebase.
Which are the most appropriate strategies for these use cases? (Choose 2.)

A. Use fine-tuning for Use Case A to ensure the model deeply learns the product manual content.

B. Use both RAG and fine-tuning for both use cases as they are always used together.

C. Use fine-tuning for Use Case B to embed the company-specific coding patterns and styles into the model's behavior.

D. Use Retrieval-Augmented Generation (RAG) for Use Case A to provide up-to-date, verifiable information at inference time.

E. Use RAG for Use Case B to allow the model to retrieve code snippets from the static codebase.

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Question 7/31

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