Databricks Generative AI Engineer Associate exam dumps

Databricks Generative AI Engineer Associate practice question 130 of 306

Databricks Certified Generative AI Engineer Associate. Free level, Databricks. Free question with the correct answer and a full explanation.

Databricks Generative AI Engineer Associate Question 130

Select 2

You are fine-tuning a prompt for a Large Language Model (LLM) in Databricks to provide detailed technical explanations instead of concise summaries. Which of the following prompt adjustments would help achieve this goal?

  1. A

    Ask the model to 'explain step-by-step with code examples where applicable.'

  2. B

    Use the phrase 'provide a one-line summary' in the prompt.

  3. C

    Include 'focus on detailed technical depth and avoid oversimplifications' in the instructions.

  4. D

    Remove all additional instructions and use a very minimal prompt.

  5. E

    Add 'summarize the topic briefly' at the end of the prompt.

Show answer and explanation

Correct answers: A, C

Explanation

To adjust an LLM's response from a baseline to a desired output, you must structure the prompt with clear and precise instructions that align with the target outcome. In this case, requesting step-by-step explanations and focusing on technical depth are key to achieving the goal of detailed responses. Conversely, asking for summaries or providing minimal instructions would deviate from the desired behavior.

  • A. Correct.

    This option encourages the model to provide detailed and step-by-step explanations, aligning with the desired output.

  • B. Incorrect.

    This option contradicts the requirement for detailed technical explanations by asking for a brief response.

  • C. Correct.

    This option explicitly instructs the model to focus on technical depth, which matches the desired output.

  • D. Incorrect.

    Removing additional instructions would result in the model reverting to its default behavior, which may not align with the desired detailed response.

  • E. Incorrect.

    This option directs the model to summarize the topic, which is opposite to the desired detailed explanation.

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