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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A development team is creating a new search application using Snowflake Cortex Search. They are currently using a 'snowflake-arctic- embed-I-v2.0' embedding model. After an initial load of 10 million rows, each with approximately 500 tokens of text, they observe a significant 'EMBED_TEXT_TOKENS' cost. They want to minimize these costs for future updates and ongoing operations. Considering their goal to optimize 'EMBED_TEXT_TOKENS' costs, which two strategies should the team prioritize for their Cortex Search Service?

A) Option A
B) Option B
C) Option E
D) Option C
E) Option D

2. An ML Engineer is logging a custom PyCaret model to the Snowflake Model Registry, with the intention of deploying it to Snowpark Container Services (SPCS) for GPU-powered inference. The PyCaret model is wrapped in a 'custom_model.ModelContext'. Which of the following statements correctly describe the considerations for the call and the model's environment?

A) Option A
B) Option B
C) Option E
D) Option C
E) Option D

3. A data pipeline processes thousands of scanned legal contracts daily using a Document AI model via the '!PREDICT function. The process involves fetching presigned URLs for documents from an internal stage using 'GET PRESIGNED URL'. Recently, the pipeline has started failing intermittently, returning the error:

The data engineering team confirms network connectivity and privileges are stable. Which of the following is the most likely cause of this issue?

A) The Document AI model build has not been published to the production environment.
B) The virtual warehouse assigned to the Document AI pipeline is undersized (e.g., X-Small), leading to slow processing that indirectly causes URL expiration.
C) The documents contain handwritten annotations, which Document AI struggles to process effectively.
D) The
E) The internal stage is not configured with

4.
Which of the following SQL snippets, when executed against a single invoice file like "invoice001 .pdf", correctly extracts and transforms the desired data, assuming 'json_content' holds the raw Document AI output?

A)

B)

C)

D)

E)

5. A data scientist has developed a Hugging Face sentence transformer model for semantic search and needs to deploy it for GPU- powered inference using Snowpark Container Services (SPCS) in Snowflake. They've already trained the SentenceTransformer model locally. Which of the following statements correctly describe essential considerations for logging and deploying this model, ensuring it leverages GPU resources and appropriate dependencies?

A) Option A
B) Option B
C) Option E
D) Option C
E) Option D

Solutions: