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Snowflake SnowPro® Specialty: Gen AI Certification Exam Sample Questions (Q57-Q62):

NEW QUESTION # 57
A development team is preparing to deploy a new Retrieval-Augmented Generation (RAG) application written in Python. They intend to use Snowflake AI Observability to capture detailed logs and traces for debugging and performance analysis. Which of the following configurations are essential prerequisites for enabling this logging capability effectively?

A. Option E
B. Option A
C. Option B
D. Option D
E. Option C

Answer: A,B,C,E

Explanation:

NEW QUESTION # 58
A data engineer is tasked with establishing a robust MLOps pipeline using the Snowflake Model Registry. They have trained a scikit-learn model and need to log it. Which of the following statements correctly describes a 'required' step or privilege for successfully logging a model using the 'Registry.log_model' method?

A. Option C
B. Option E
C. Option B
D. Option A
E. Option D

Answer: C

Explanation:

NEW QUESTION # 59
A data science team is developing an internal LLM to classify legal documents. They previously used a general-purpose LLM, but found its performance for their specific legal domain to be inconsistent, leading to high error rates and increased manual review. They decide to fine-tune a model using Snowflake Cortex Fine-tuning to improve accuracy and reduce latency for real-time document classification. Which base model, among those available for fine-tuning via SNOWFLAKE .CORTEX.FINETUNE
, is explicitly noted for its low latency and high throughput processing, making it a strong candidate for this use case, especially for multi-page text classification?

A. Option B
B. Option D
C. Option C
D. Option E
E. Option A

Answer: B

Explanation:
Option D is correct. The sources explicitly state that
mistral-7b
is 'ideal for your simplest summarization, structuration, and question answering tasks that need to be done quickly. It offers low latency and high throughput processing for multiple pages of text with its 32K context window'. This description directly aligns with the scenario's requirement for improved accuracy and reduced latency for real-time document classification, particularly for multi-page legal documents. Option A is incorrect because while

is available for fine-tuning and suitable for content creation and chat applications, it is not specifically noted for low latency and high throughput processing for multi-page text classification in the same way as

is Snowflake's top-tier enterprise LLM excelling at SQL generation, coding, and instruction following, but it is not listed as a base model available for fine-tuning with SNOWF LAKE .CORTEX.FINETUNE .

NEW QUESTION # 60
A Data Engineer is responsible for deploying machine learning models using Snowpark Container Services. They need to ensure that a specific role, model_deployer_role, has the appropriate permissions to create a Snowpark Container Service that uses an image from an existing image repository named my_inferenc_ images. Which of the following SQL commands grant the necessary privileges 'on the image repository' for this purpose?

Answer: C,D

Explanation:
Option D is correct because the privilege allows a role to read images from the repository, which is READ ON IMAGE REPOSITORY fundamental for creating a service that uses those images. Option E is correct because the privilege is SERVICE READ ON IMAGE REPOSITORY specifically identified as being for services that need to use images from the repository. Option A is incorrect as is a general USAGE ON DATABASE privilege for database access, not a specific privilege on the image repository for using its images. Option B is incorrect because CREATE SERVICE ON is required to create the service object in a schema, but it is a privilege on the 'schema' itself, not directly on the 'image repository' for SCHEMA accessing its content. Option C is incorrect because is used for pushing or uploading images to the repository, not for WRITE ON IPtAGE REPOSITORY consuming them when creating a service.

NEW QUESTION # 61
A data team is designing a new Cortex Analyst application and wants to ensure optimal performance, accuracy, and user experience for text-to-SQL conversions. They are particularly interested in how custom instructions interact with other semantic model features and LLM functionalities. Which of the following statements about using in Cortex Analyst are accurate?

A. The 'custom_instructions' in a semantic model directly influence the underlying Large Language Model (LLM) to generate SQL queries that align with specified business context or formatting preferences.
B. Custom instructions are primarily used to define new logical tables or dimensions within the semantic model, effectively extending the data model at runtime.
C. The presence of 'custom_instructions' in a semantic model can potentially increase the token count for Cortex Analyst requests, as the instructions are passed as additional context to the LLM.
D. Using detailed 'custom_instructions' can help mitigate issues where the LLM might struggle with domain-specific terminology or complex business logic not explicitly defined in column descriptions.
E. When both 'custom_instructionS and a highly relevant 'verified_query' exist for a user's question, Cortex Analyst will always prioritize the directives from the 'custom_instructions' over the SQL provided in the 'verified_querv'.

Answer: A,D

Explanation:
Option A is correct because custom instructions provide unique business context to the LLM, enabling greater control over the generated SQL queries to align with specific business needs or formatting. Option C is also correct because by providing business context to the LLM via custom instructions, the model can better handle domain-specific terminology or complex business logic, improving accuracy. Option B is incorrect; a 'verified_querv' provides a *pre-written and verified SQL query* for a specific question. If a user's question is similar to a verified query, Cortex Analyst typically uses that query, potentially overriding or prioritizing it over general 'custom_instructions' for that specific scenario, as verified queries are explicit answers. The sources imply that verified queries are a direct solution for known questions, while custom instructions provide general guidance. Option D is incorrect for Cortex Analyst; the credit rate usage is based on the number of messages processed, not the number of tokens, so the length of custom instructions doesn't directly affect cost via token count. Option E is incorrect as 'custom_instructions' are for guiding SQL generation, not for defining or extending the semantic model's structure (logical tables, dimensions).

NEW QUESTION # 62
......

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