Databricks-Generative-AI-Engineer-Associate試験無料問題集（63題）「Databricks Certified Generative AI Engineer Associate 認定」

出題：1

A Generative Al Engineer has built an LLM-based system that will automatically translate user text between two languages. They now want to benchmark multiple LLM's on this task and pick the best one. They have an evaluation set with known high quality translation examples. They want to evaluate each LLM using the evaluation set with a performant metric.
Which metric should they choose for this evaluation?

A. RECALL metric

B. BLEU metric

C. ROUGE metric

D. NDCG metric

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

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. Number of customer inquiries processed per unit of time

D. Final perplexity scores for the training of the model

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

A Generative Al Engineer is developing a RAG application and would like to experiment with different embedding models to improve the application performance.
Which strategy for picking an embedding model should they choose?

A. Pick an embedding model with multilingual support to support potential multilingual user questions

B. Pick the most recent and most performant open LLM released at the time

C. Pick an embedding model trained on related domain knowledge

D. pick the embedding model ranked highest on the Massive Text Embedding Benchmark (MTEB) leaderboard hosted by HuggingFace

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

A Generative AI Engineer has been asked to build an LLM-based question-answering application. The application should take into account new documents that are frequently published. The engineer wants to build this application with the least cost and least development effort and have it operate at the lowest cost possible.
Which combination of chaining components and configuration meets these requirements?

A. The LLM needs to be frequently with the new documents in order to provide most up-to-date answers.

B. For the application a prompt, a retriever, and an LLM are required. The retriever output is inserted into the prompt which is given to the LLM to generate answers.

C. For the question-answering application, prompt engineering and an LLM are required to generate answers.

D. For the application a prompt, an agent and a fine-tuned LLM are required. The agent is used by the LLM to retrieve relevant content that is inserted into the prompt which is given to the LLM to generate answers.

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

A Generative AI Engineer wants to build an LLM-based solution to help a restaurant improve its online customer experience with bookings by automatically handling common customer inquiries. The goal of the solution is to minimize escalations to human intervention and phone calls while maintaining a personalized interaction. To design the solution, the Generative AI Engineer needs to define the input data to the LLM and the task it should perform.
Which input/output pair will support their goal?

A. Input: Online chat logs; Output: Buttons that represent choices for booking details

B. Input: Customer reviews; Output: Classify review sentiment

C. Input: Online chat logs; Output: Cancellation options

D. Input: Online chat logs; Output: Group the chat logs by users, followed by summarizing each user's interactions

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：6

A Generative Al Engineer is using an LLM to classify species of edible mushrooms based on text descriptions of certain features. The model is returning accurate responses in testing and the Generative Al Engineer is confident they have the correct list of possible labels, but the output frequently contains additional reasoning in the answer when the Generative Al Engineer only wants to return the label with no additional text.
Which action should they take to elicit the desired behavior from this LLM?

A. Use zero shot chain-of-thought prompting to prevent a verbose output format

B. Use a system prompt to instruct the model to be succinct in its answer

C. Use zero shot prompting to instruct the model on expected output format

D. Use few snot prompting to instruct the model on expected output format

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

Databricks-Generative-AI-Engineer-Associate試験無料問題集「Databricks Certified Generative AI Engineer Associate 認定」