1Z0-1127 Practice Test 11 — 15 Questions

Question 1

A company wants to deploy a custom fine-tuned model for retrieval-augmented generation (RAG) using dedicated AI cluster. They need to ensure the model can handle concurrent requests from multiple applications with consistent latency. What should they configure?

Accepted Answer

Increase the number of replicas in the dedicated cluster.. Option A is correct because increasing the number of replicas in the dedicated cluster distributes the load across multiple model copies, improving concurrency and latency stability.

Answer

Set a high temperature to keep responses concise.

Answer

Enable auto-scaling on the cluster.

Answer

Use the managed serving endpoint instead.

Question 2

A financial institution wants to use OCI Generative AI to analyze sensitive customer documents. They need to ensure no data leaves OCI and the model is fine-tuned on their proprietary data. Which deployment option should they choose?

Accepted Answer

Dedicated AI cluster with private endpoint.. Option A is correct because a dedicated AI cluster with private endpoint keeps data within OCI and allows fine-tuning on proprietary data. Option B is wrong because serverless inference does not support fine-tuning. Option C is wrong because OCI Data Science notebook sessions are for development, not production. Option D is wrong because OCI Functions are for event-driven compute, not fine-tuning.

Answer

Serverless inference with data isolation.

Answer

OCI Functions with GPU.

Answer

OCI Data Science notebook session.

Question 3

Refer to the exhibit. A user runs 'oci generative-ai model list' and sees this output. They then try to use 'cohere.command-light' but get an error. What is the most likely reason?

Accepted Answer

The model is in INACTIVE state. Option B is correct because the model 'cohere.command-light' has lifecycle-state 'INACTIVE', meaning it cannot be used. Option A is false because it is listed; C and D would produce different errors.

Answer

The API key does not have access

Answer

The model is not listed

Answer

The region is wrong

Question 4

A company is deploying a customer-facing chatbot using OCI Generative AI. They need to prevent the model from generating offensive or harmful content. Which feature should they implement?

Accepted Answer

Enable OCI Generative AI guardrails with content filtering.. OCI GenAI guardrails provide built-in content filtering to block harmful outputs.

Answer

Custom post-processing to scan each response.

Answer

Limit the user input length.

Answer

Use a smaller model that is less capable of generating harm.

Question 5

Which TWO actions are required to use a custom fine-tuned model via OCI Generative AI? (Choose two.)

Accepted Answer

Deploy the model to an endpoint. Options B and D are required. B: Fine-tuning must be complete. D: Model endpoint must be deployed. A is optional (private endpoint). C is not needed if within same region. E is not required unless cross-tenant.

Answer

Provision a private endpoint for the model

Answer

Enable cross-region replication

Answer

Grant access to other tenancies

Question 6

Refer to the exhibit. A user runs this command and gets an error: 'InvalidParameter: unit-shape 'GPU.1' is not supported in this region. Supported shapes: GPU.2, GPU.4'. What should the user do?

Accepted Answer

Use unit-shape GPU.2. Option B is correct because the error indicates GPU.1 is unsupported, and GPU.2 is listed as supported. Changing region (A) may work but is unnecessary; increasing unit count (C) or changing compartment (D) will not resolve the shape issue.

Answer

Increase unit count

Answer

Change compartment

Answer

Use a different region

Question 7

Which TWO are benefits of using dedicated AI clusters for OCI Generative AI?

Accepted Answer

Guaranteed throughput. Dedicated AI clusters provide predictable latency and guaranteed throughput because they are single-tenant.

Answer

Automatic model updates

Answer

Lower cost than on-demand for all workloads

Answer

No need to manage scaling

Question 8

Refer to the exhibit. The group DataScientists can run inference but cannot fine-tune a model on a dedicated AI cluster. Which additional policy statement is required to allow fine-tuning?

Accepted Answer

Allow group DataScientists to manage dedicated-ai-clusters in compartment ABC. Fine-tuning requires manage permission on dedicated-ai-clusters to create and manage fine-tuning jobs.

Answer

Allow group DataScientists to inspect dedicated-ai-clusters in compartment ABC

Answer

Allow group DataScientists to use generative-ai-fine-tune in compartment ABC

Answer

Allow group DataScientists to use dedicated-ai-clusters in compartment ABC

Question 9

Refer to the exhibit. In this RAG pipeline, what is the role of the 'embedding_model' variable?

Accepted Answer

It converts text into vector representations for similarity search.. The embedding model converts text into numerical vector representations that can be stored and searched for similarity.

Answer

It applies guardrails to filter content.

Answer

It fine-tunes the model on the provided texts.

Answer

It generates text completions based on prompts.

Question 10

A healthcare company wants to use OCI Generative AI to summarize patient medical records while ensuring PHI compliance. Which OCI service feature should they enable?

Accepted Answer

Use the data masking capability within OCI Generative AI. Option B is correct: Data masking helps redact PHI. Option A (VCN) is network, not data masking. Option C (IAM) is access control. Option D (WAF) is web security.

Answer

Configure a Virtual Cloud Network (VCN) with private subnets

Answer

Deploy a Web Application Firewall (WAF) in front of the API

Answer

Set up Identity and Access Management (IAM) policies to restrict access

Question 11

An enterprise is fine-tuning a Cohere model using OCI Generative AI for a domain-specific task. After training, the model shows high accuracy on validation data but poor performance on unseen test data. What is the most likely cause?

Accepted Answer

The model overfitted to training data. Option D is correct: Overfitting occurs when model learns training data too well. Option A (learning rate) is possible but overfitting is more indicative. Option B (dataset size) could cause underfitting, not overfitting. Option C (epochs) too many can cause overfitting, but the symptom matches D.

Answer

The training dataset was too small

Answer

The number of training epochs was too low

Answer

The learning rate was set too high

Question 12

A developer wants to generate text embeddings using OCI Generative AI. Which model endpoint should they call?

Accepted Answer

POST /v1/embed. Option C is correct: The embed endpoint is for generating embeddings. Option A (generate) is for text generation. Option B (summarize) is for summarization. Option D (chat) is for conversation.

Answer

POST /v1/generate

Answer

POST /v1/summarize

Answer

POST /v1/chat

Question 13

A company is using OCI Generative AI for customer support chatbots. They notice that responses sometimes include offensive content. Which built-in safety feature should they configure?

Accepted Answer

Content moderation filters. Option A is correct: Content moderation filters block harmful content. Option B (temperature) controls randomness, not safety. Option C (max tokens) limits length. Option D (stop sequences) stops generation at specific tokens.

Answer

Configure stop sequences

Answer

Set a maximum token limit

Answer

Adjust the temperature parameter

Question 14

A data scientist is fine-tuning a model on OCI Generative AI with a custom dataset. They receive a "QuotaExceeded" error during training. What is the most likely cause?

Accepted Answer

Exceeded the training compute unit quota. Option B is correct: Fine-tuning consumes training compute units, which have quota limits. Option A (API call rate) is for API requests. Option C (model storage) is for storing models. Option D (data transfer) is for egress.

Answer

Exceeded the API call rate limit

Answer

Exceeded the model storage limit

Answer

Exceeded the data transfer out limit

Question 15

Which OCI Generative AI parameter controls the diversity of generated text by increasing the probability of less likely tokens?

Accepted Answer

temperature. Option C is correct: Temperature above 1 increases randomness. Option A (top_p) is nucleus sampling, option B (top_k) limits to top K tokens, option D (frequency_penalty) reduces repetition.

Answer

frequency_penalty

Answer

top_k

Answer

top_p