최신Databricks Certified Generative AI Engineer Associate - Databricks-Generative-AI-Engineer-Associate무료샘플문제

A. The similarity to the previous language

B. The ability to generate responses in code

C. The accuracy and relevance of the responses

D. The latency of the response and the length of text generated

A. AutoML

B. Feature Serving

C. Foundation Model APIs

D. DatabrickslQ

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

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

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

C. 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.

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.

A. Response-generating LLM

B. Vector database

C. Invite users to submit long, rather than concise, questions

D. Embedding model

A. RECALL metric

B. NDCG metric

C. ROUGE metric

D. BLEU metric

A. Retrain the response generating model using ALiBi

B. Use a smaller embedding model to generate

C. Decrease the chunk size of embedded documents

D. Reduce the maximum output tokens of the new model

E. Reduce the number of records retrieved from the vector database

A. Keep all articles because the RAG application needs to understand non-company content to avoid answering questions about them.

B. Consolidate all SnoPen AI related documents into a single chunk in the vector database.

C. Include in the system prompt that any information it sees will be about SnoPenAI, even if no data filtering is performed.

D. Include in the system prompt that the application is not supposed to answer any questions unrelated to SnoPen Al.