최신 Databricks-Generative-AI-Engineer-Associate 무료덤프 - Databricks Certified Generative AI Engineer Associate

문제1

A Generative AI Engineer just deployed an LLM application at a digital marketing company that assists with answering customer service inquiries.
Which metric should they monitor for their customer service LLM application in production?

A. Energy usage per query

B. HuggingFace Leaderboard values for the base LLM

C. Final perplexity scores for the training of the model

D. Number of customer inquiries processed per unit of time

정답: D

설명: (DumpTOP 회원만 볼 수 있음)

문제2

A Generative Al Engineer has already trained an LLM on Databricks and it is now ready to be deployed.
Which of the following steps correctly outlines the easiest process for deploying a model on Databricks?

A. Log the model using MLflow during training, directly register the model to Unity Catalog using the MLflow API, and start a serving endpoint

B. Log the model as a pickle object, upload the object to Unity Catalog Volume, register it to Unity Catalog using MLflow, and start a serving endpoint

C. Wrap the LLM's prediction function into a Flask application and serve using Gunicorn

D. Save the model along with its dependencies in a local directory, build the Docker image, and run the Docker container

정답: A

문제3

A Generative AI Engineer is building an LLM to generate article summaries in the form of a type of poem, such as a haiku, given the article content. However, the initial output from the LLM does not match the desired tone or style.
Which approach will NOT improve the LLM's response to achieve the desired response?

A. Provide the LLM with a prompt that explicitly instructs it to generate text in the desired tone and style

B. Use a neutralizer to normalize the tone and style of the underlying documents

C. Include few-shot examples in the prompt to the LLM

D. Fine-tune the LLM on a dataset of desired tone and style

정답: B

설명: (DumpTOP 회원만 볼 수 있음)

문제4

A Generative AI Engineer is tasked with deploying an application that takes advantage of a custom MLflow Pyfunc model to return some interim results.
How should they configure the endpoint to pass the secrets and credentials?

A. Pass variables using the Databricks Feature Store API

B. Add credentials using environment variables

C. Use spark.conf.set ()

D. Pass the secrets in plain text

정답: B

설명: (DumpTOP 회원만 볼 수 있음)

문제5

A Generative Al Engineer has successfully ingested unstructured documents and chunked them by document sections. They would like to store the chunks in a Vector Search index. The current format of the dataframe has two columns: (i) original document file name (ii) an array of text chunks for each document.
What is the most performant way to store this dataframe?

A. Store each chunk as an independent JSON file in Unity Catalog Volume. For each JSON file, the key is the document section name and the value is the array of text chunks for that section

B. Flatten the dataframe to one chunk per row, create a unique identifier for each row, and save to a Delta table

C. First create a unique identifier for each document, then save to a Delta table

D. Split the data into train and test set, create a unique identifier for each document, then save to a Delta table

정답: B

설명: (DumpTOP 회원만 볼 수 있음)

문제6

A Generative AI Engineer is developing an LLM application that users can use to generate personalized birthday poems based on their names.
Which technique would be most effective in safeguarding the application, given the potential for malicious user inputs?

A. Increase the amount of compute that powers the LLM to process input faster

B. Ask the LLM to remind the user that the input is malicious but continue the conversation with the user

C. Implement a safety filter that detects any harmful inputs and ask the LLM to respond that it is unable to assist

D. Reduce the time that the users can interact with the LLM

정답: C

설명: (DumpTOP 회원만 볼 수 있음)

최신 Databricks-Generative-AI-Engineer-Associate 무료덤프 - Databricks Certified Generative AI Engineer Associate

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