1Z0-1127 OCI Generative AI Service — All Questions With Answers

Question 1mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 2easymultiple choice

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You need to convert a set of customer support tickets into vector embeddings for a similarity search application. Which OCI Generative AI model should you use?

Question 3mediummultiple choice

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A data scientist has fine-tuned a Cohere Command R model using the T-Few technique. They now need to deploy this custom model for real-time inference with low latency. What is the recommended deployment option in OCI Generative AI?

Question 4hardmultiple choice

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A developer is using the OCI Generative AI Chat API with Cohere Command R+ to build a multi-turn conversational agent. They want the agent to always respond in a formal tone, regardless of the user's phrasing. Which parameter should they set in the API request to achieve this consistently?

Question 5mediummultiple choice

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A company uses OCI Generative AI Agents to build a RAG application that answers questions from documents stored in OCI Object Storage. The knowledge base is updated daily. Which step is necessary to ensure the agent incorporates the latest documents?

Question 6easymultiple choice

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You want to test different prompts and parameters (temperature, max tokens) for a summarization task using a foundation model without writing any code. Which OCI tool should you use?

Question 7mediummultiple choice

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A security administrator needs to grant a data science team access to use OCI Generative AI resources (e.g., run inference, create fine-tuning jobs) but only within a specific compartment. What is the correct IAM policy statement?

Question 8hardmultiple choice

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A team is fine-tuning a Llama 3 model using OCI Generative AI. The training dataset contains 10,000 prompt-completion pairs in JSONL format. After submitting the fine-tuning job, it fails with a 'Data validation error'. What is the most likely cause?

Question 9mediummultiple choice

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An application needs to generate embeddings for text in multiple languages (English, Spanish, French). Which OCI Generative AI embedding model should be used?

Question 10easymultiple choice

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You are using the OCI Generative AI Playground with a Cohere Command R model. You want the model to generate more varied and creative responses. Which parameter should you increase?

Question 11hardmultiple choice

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A developer is using the OCI Generative AI Generate API (not Chat API) to create a single-turn text completion. They need to include a system-level instruction that guides the model's behavior for that request. Which parameter should they use?

Question 12mediummultiple choice

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A company wants to use OCI Generative AI Agents for a question-answering system over their internal knowledge base stored in OCI Object Storage. The data consists of PDF and Word documents. What is the first step to make this data usable by the agent?

Question 13mediummulti select

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A company wants to reduce costs for a high-volume, latency-tolerant text generation workload using OCI Generative AI. Which TWO strategies should they consider?

Question 14mediummulti select

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A developer is building a RAG application using OCI Generative AI Agents. They want to ensure the agent only retrieves information from approved documents in a specific compartment. Which THREE steps are required?

Question 15hardmulti select

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A machine learning engineer is fine-tuning a Cohere Command R model using OCI Generative AI. They want to evaluate the fine-tuned model's performance before deploying. Which TWO methods can they use?

Question 16mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 17mediummultiple choice

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A data scientist needs to create vector embeddings for a multilingual customer feedback dataset to perform clustering analysis. Which OCI Generative AI embedding model should they choose?

Question 18easymultiple choice

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What is the primary benefit of using a Dedicated AI Cluster for inference in OCI Generative AI?

Question 19hardmultiple choice

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A team fine-tuned a Cohere Command R model using the T-Few technique on a dataset of JSONL prompt/completion pairs. After deployment, they observe that the model's responses are too repetitive. Which parameter adjustment in the OCI Generative AI Playground would BEST address this issue?

Question 20mediummultiple choice

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An organization wants to allow its data science group to use OCI Generative AI services but restrict access to a specific compartment. Which IAM policy statement correctly achieves this?

Question 21mediummultiple choice

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A developer is using the OCI Generative AI Chat API to build a multi-turn conversational assistant. They want the assistant to adopt a formal tone throughout the conversation. Which parameter should they set in the API request to achieve this?

Question 22easymultiple choice

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Which OCI Generative AI model is specifically designed to generate embeddings for English text?

Question 23hardmultiple choice

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A team fine-tuned a model using T-Few and validated it. They now want to deploy this fine-tuned model to a dedicated AI cluster for low-latency inference. What must they do FIRST?

Question 24mediummultiple choice

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A user wants to test different prompt variations with a generative model interactively without writing code. Which OCI Generative AI tool should they use?

Question 25hardmultiple choice

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An organization needs to fine-tune a Cohere Command R model for a custom domain. They have prepared a dataset in JSONL format. Which component of the fine-tuning job specifies the base model and the training dataset location?

Question 26easymultiple choice

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Which OCI Generative AI service component is designed to convert text into vector representations for use in semantic search?

Question 27mediummultiple choice

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A company wants to build a RAG-based assistant that answers queries using documents stored in OCI Object Storage. Which OCI Generative AI service should they use?

Question 28mediummulti select

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A data scientist needs to generate embeddings for a collection of documents to be used for both clustering and semantic search. They want to use appropriate input types for each task. Which TWO input types should they use from the Cohere Embed API? (Choose two.)

Question 29mediummulti select

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A team is planning to use OCI Generative AI to summarize large documents. They need to choose between on-demand (pay-as-you-go) and dedicated cluster pricing. Which THREE factors should they consider when deciding? (Choose three.)

Question 30hardmulti select

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A machine learning engineer is fine-tuning a Cohere Command R model using T-Few. They need to prepare the training dataset in the correct format. Which TWO statements about the dataset format are true? (Choose two.)

Question 31mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 32easymultiple choice

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Which OCI Generative AI model is best suited for generating embeddings from text that can be used for semantic search across multiple languages?

Question 33mediummultiple choice

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A data scientist wants to fine-tune a Cohere Command R model using the T-Few technique. They have prepared a dataset in JSONL format with prompt/completion pairs. Which step is REQUIRED before creating the fine-tuning job?

Question 34hardmultiple choice

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An organization requires low-latency inference for a custom fine-tuned model deployed on OCI Generative AI. The model must be isolated from other tenants. Which infrastructure choice meets these requirements?

Question 35easymultiple choice

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In the OCI Generative AI Playground, a developer wants to control how creative the model responses are. Which parameter should they adjust?

Question 36mediummultiple choice

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A financial services firm needs to ensure that only members of the 'DataScientists' group can use OCI Generative AI resources in the 'prod' compartment. Which IAM policy statement should be applied?

Question 37mediummultiple choice

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A developer uses the OCI Generative AI Chat API to build a multi-turn conversational agent. They notice the model starts to lose context after several exchanges. What is the MOST likely cause?

Question 38hardmultiple choice

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A company is building a document summarization pipeline using OCI Generative AI. They need to summarize thousands of legal documents efficiently. Which approach minimizes cost while maintaining quality?

Question 39easymultiple choice

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Which OCI Generative AI model would you use to reorder search results to improve relevance ranking?

Question 40mediummultiple choice

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A team wants to use OCI Generative AI Agents to build a RAG system that answers questions from documents stored in OCI Object Storage. What must they create first?

Question 41hardmultiple choice

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During fine-tuning, a user notices the loss does not decrease after several epochs. The dataset is a JSONL file with 500 prompt/completion pairs. What is the MOST likely cause?

Question 42mediummultiple choice

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An application needs to generate embeddings for customer reviews to cluster them by sentiment. Which input type should be specified in the Embedding API call?

Question 43mediummulti select

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A developer is using the OCI Generative AI Chat API to create a customer support bot. They want the bot to maintain a consistent personality and follow specific guidelines. Which TWO settings should they use?

Question 44hardmulti select

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A company wants to deploy a fine-tuned model for real-time inference with consistent low latency. They are evaluating dedicated AI clusters. Which THREE factors should they consider when provisioning the cluster?

Question 45easymulti select

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Which TWO OCI Generative AI features are available in the Playground for testing models?

Question 46mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 47easymultiple choice

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Which OCI Generative AI model family is specifically designed to convert text into vector embeddings for semantic search and clustering tasks?

Question 48mediummultiple choice

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A data scientist is using the OCI Generative AI Playground to test a summarization model. They want to generate shorter summaries and avoid repetitive phrasing. Which parameter adjustments should they make?

Question 49hardmultiple choice

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An organization needs to deploy a fine-tuned model for real-time inference with strict latency requirements. They have provisioned a Dedicated AI Cluster with 2 model units. Which statement about this setup is accurate?

Question 50mediummultiple choice

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A developer is fine-tuning a Cohere Command R model using OCI Data Science and the T-Few technique. They have prepared a dataset. What is the required format for the training data?

Question 51mediummultiple choice

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A security administrator needs to grant a group of data scientists the ability to use OCI Generative AI service resources in the compartment 'genai-dev'. They want to allow the group to create endpoints and run inference, but not to manage IAM policies. Which policy statement is correct?

Question 52hardmultiple choice

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During a fine-tuning job for a text generation model, the loss curve shows that the training loss decreases steadily, but the evaluation loss increases after a few epochs. Which action is most likely to improve the model's generalization?

Question 53easymultiple choice

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Which OCI Generative AI API is used to send a message and receive a model-generated response while maintaining a conversation history?

Question 54mediummultiple choice

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A team is building a multilingual semantic search application. They need to index documents in English, Spanish, and French, and later search using queries in any of these languages. Which embedding model should they use?

Question 55mediummultiple choice

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A developer is using the OCI Generative AI Agents service to build a RAG application. They have uploaded policy PDFs to an OCI Object Storage bucket. What is the next step to make the documents searchable?

Question 56hardmultiple choice

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An organization wants to use OCI Generative AI for a high-volume summarization workload. They estimate 10 million tokens per month and need consistent low latency. Which pricing model is most cost-effective?

Question 57easymultiple choice

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Which statement accurately describes the T-Few fine-tuning technique used in OCI Generative AI?

Question 58mediummulti select

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A company wants to implement a retrieval-augmented generation (RAG) chatbot using OCI Generative AI Agents. Which TWO services or components are required for this solution?

Question 59hardmulti select

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A developer is building a multi-turn chatbot using the OCI Generative AI Chat API. Which THREE parameters or features should they configure to maintain coherent conversation history?

Question 60mediummulti select

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A data scientist is using the OCI Generative AI Embeddings API to generate vectors for a classification task. Which TWO input types are appropriate for this use case?

Question 61easymultiple choice

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An OCI Generative AI user wants to host a fine-tuned model with guaranteed low latency for a production application. Which option should they choose?

Question 62mediummultiple choice

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A data scientist is fine-tuning a model using T-Few in OCI Generative AI. They have prepared a dataset with prompt/completion pairs. Which file format is required for the training data upload?

Question 63mediummultiple choice

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A company needs to generate vector embeddings for a multilingual document set to support semantic search across English and French documents. Which embedding model should they use?

Question 64hardmultiple choice

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An administrator wants to grant a group of data scientists permission to use OCI Generative AI resources in a specific compartment, but prevent them from creating Dedicated AI Clusters. Which IAM policy statement achieves this?

Question 65mediummultiple choice

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A developer is using the OCI Generative AI Chat API to build a conversational assistant. They want the assistant to adopt a formal tone regardless of user input. Which parameter should they set in the API request?

Question 66easymultiple choice

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A user wants to quickly test different prompts and parameters (temperature, max tokens) with various OCI Generative AI models without writing any code. Which tool should they use?

Question 67mediummultiple choice

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A company wants to use OCI Generative AI Agents to build a RAG application over documents stored in OCI Object Storage. What must they create first?

Question 68hardmultiple choice

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During fine-tuning a model using T-Few in OCI Generative AI, the job fails with a 'dataset format error'. The training dataset is a JSONL file. Which of the following is the MOST likely cause?

Question 69mediummultiple choice

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A developer needs to generate embeddings for a set of search queries to be used in a semantic search system. Which input type should they specify when calling the Embedding API?

Question 70easymultiple choice

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Which OCI Generative AI model is designed to rerank and improve the relevance of documents retrieved by a search system?

Question 71mediummultiple choice

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An organization wants to use OCI Generative AI for summarizing long legal documents. Which OCI Generative AI service component is specifically designed for this task?

Question 72hardmultiple choice

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A team fine-tuned a Cohere Command R model in OCI GenAI and validated it. They now need to deploy it for production inference with a dedicated endpoint. What is the correct sequence of steps?

Question 73mediummulti select

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A data scientist is configuring a fine-tuning job in OCI Generative AI. Which TWO of the following are required inputs for creating the job?

Question 74mediummulti select

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A company wants to use OCI Generative AI Agents to create a RAG-powered customer support system. Which THREE components are essential for the agent to work?

Question 75hardmulti select

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An administrator is creating IAM policies for OCI Generative AI. They want to allow a group of developers to use (invoke) models and manage endpoints, but NOT create or delete Dedicated AI Clusters. Which TWO policy statements should be combined?

Question 76mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 77easymultiple choice

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Which OCI Generative AI service component is specifically designed to convert text into vector representations for use in semantic search and clustering?

Question 78mediummultiple choice

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A data scientist needs to fine-tune a model using OCI Generative AI. They have prepared a dataset in JSONL format with prompt/completion pairs. The fine-tuning job is configured with the T-Few technique. What is a key characteristic of T-Few fine-tuning?

Question 79hardmultiple choice

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An organization is deploying a custom fine-tuned model for a real-time fraud detection application. The model must respond within 200ms and cannot share infrastructure with other customers. Which OCI GenAI infrastructure option should they choose?

Question 80mediummultiple choice

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A developer is using the OCI GenAI Playground to test a summarisation model. They want the summary to be concise and less creative. Which combination of parameter adjustments would best achieve this?

Question 81mediummultiple choice

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A team wants to use OCI Generative AI Agents to build a question-answering system over documents stored in OCI Object Storage. They have created a knowledge base and are ready to test. Which API should they use to interact with the agent for multi-turn conversations?

Question 82easymultiple choice

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Which of the following is NOT an available model in OCI Generative AI service?

Question 83hardmultiple choice

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A security engineer needs to allow the DataScience group to use OCI Generative AI resources (Chat, Embedding, and Summarisation) in the compartment 'genai-compartment', but not allow them to create dedicated AI clusters. Which IAM policy statement achieves this?

Question 84mediummultiple choice

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A developer is using the OCI GenAI Chat API to build a multi-turn customer support chatbot. They want the assistant to always introduce itself as 'SupportBot' and never mention being an AI. How should they configure the API call?

Question 85easymultiple choice

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Which input type should be used with the Cohere Embed API when generating embeddings for a query in a semantic search system?

Question 86hardmultiple choice

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A company has fine-tuned a Cohere Command R model using T-Few and wants to deploy it for real-time inference with the lowest possible latency. They have provisioned a dedicated AI cluster with 2 model units. However, latency is still higher than expected. Which action is MOST likely to reduce latency?

Question 87mediummultiple choice

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A data scientist is creating a fine-tuning job in OCI Generative AI. They have prepared a JSONL dataset with prompt/completion pairs. What is the correct format for each line in the JSONL file?

Question 88mediummulti select

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A company wants to use OCI Generative AI to build a multilingual customer support chatbot. They need to understand customer queries in multiple languages and generate responses in the same language. Which TWO actions should they take? (Choose two.)

Question 89hardmulti select

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A financial services company must deploy a fine-tuned model for transaction categorization. The model must be isolated from other tenants and provide predictable low-latency inference. The compliance team also requires that training data never leaves the OCI tenancy. Which THREE steps should the team take? (Choose three.)

Question 90easymulti select

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Which TWO statements accurately describe the OCI Generative AI Playground? (Choose two.)

Question 91mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 92easymultiple choice

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Which OCI Generative AI API should be used to convert a user's query into a vector representation for semantic search?

Question 93mediummultiple choice

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A data scientist needs to fine-tune a large language model on a custom dataset of 10,000 prompt-completion pairs. They want to minimize cost while still updating the model effectively. Which fine-tuning technique is used by OCI Generative AI service?

Question 94hardmultiple choice

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An organization requires low-latency inference for a custom fine-tuned model that will be used in a real-time application. They also need guaranteed availability and isolation from other tenants. Which infrastructure option should they choose?

Question 95mediummultiple choice

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A developer is using the OCI Generative AI Playground to test a Cohere Command R model. They want to reduce repetitiveness in the generated responses. Which parameter should they increase?

Question 96mediummultiple choice

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A regulatory compliance team needs to restrict access to the OCI Generative AI service so that only users in the 'AI_Engineers' group can create fine-tuning jobs and endpoints. Which IAM policy statement should be used?

Question 97hardmultiple choice

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A developer is using the Chat API for a multi-turn conversation. They want the assistant to adopt a formal tone and always identify itself as 'OracleBot'. How should they configure the API request?

Question 98easymultiple choice

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Which OCI Generative AI model family is specifically designed for reranking search results to improve relevance?

Question 99mediummultiple choice

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A machine learning engineer is preparing a dataset for fine-tuning a model in OCI Generative AI. The dataset consists of customer support conversations with questions and desired answers. What is the required format for the training data?

Question 100mediummultiple choice

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A company wants to use OCI Generative AI Agents to build a question-answering system over documents stored in OCI Object Storage. Which component acts as the knowledge source for the agent?

Question 101hardmultiple choice

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During fine-tuning a model in OCI Generative AI, the training loss does not decrease after several epochs. The dataset has 5,000 prompt-completion pairs. What is the MOST likely cause?

Question 102easymultiple choice

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Which OCI Generative AI API should be used to generate a summary of a long legal document?

Question 103mediummulti select

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A developer is building a multilingual search application and needs to generate embeddings for user queries in multiple languages. Which two options are correct? (Select TWO)

Question 104hardmulti select

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An enterprise needs to deploy a custom fine-tuned model for real-time inference with strict latency requirements. They also need to manage costs by paying only for usage. Which three steps are required to achieve this? (Select THREE)

Question 105mediummulti select

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A company is using OCI Generative AI Agents to build a customer support assistant. They have uploaded product manuals to OCI Object Storage. Which two components are required to create the agent? (Select TWO)

Question 106easymultiple choice

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Which OCI Generative AI model family is optimized for generating text embeddings that capture semantic meaning for tasks like clustering and classification?

Question 107easymultiple choice

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A developer wants to interactively test different prompts and parameters (temperature, top_p, frequency_penalty) with a Cohere Command R model before integrating it into an application. Which tool should they use?

Question 108mediummultiple choice

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A data scientist needs to fine-tune a Llama 3 model for a legal document classification task. They have a dataset of 10,000 labeled examples. Which fine-tuning technique available in OCI Generative AI is most suitable for efficiently adapting the model with limited computational overhead?

Question 109mediummultiple choice

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An organization plans to deploy a custom fine-tuned model for a real-time chat application requiring consistent low-latency responses. They expect high throughput during business hours. Which OCI Generative AI infrastructure choice best meets these requirements?

Question 110mediummultiple choice

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A developer is building a summarization pipeline using OCI Generative AI. They want to ensure the summary includes key points from the entire document without truncation. Which parameter should they primarily adjust?

Question 111mediummultiple choice

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A security administrator needs to grant a group of data scientists access to use OCI Generative AI resources (models, endpoints) in compartment 'GenAI-Prod', but not allow them to create or manage infrastructure. Which IAM policy statement should be used?

Question 112hardmultiple choice

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A team has fine-tuned a Cohere Command R model using T-Few on a dataset of 5,000 prompt/completion pairs. After deployment, they notice the model sometimes generates off-topic responses. Which action is most likely to improve response relevance without requiring new training data?

Question 113mediummultiple choice

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A developer is using the OCI Generative AI Chat API to build a multi-turn conversational agent. They want the model to remember previous exchanges within the same session. How should they manage conversation history?

Question 114easymultiple choice

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Which OCI Generative AI service component is specifically designed to convert text into numerical vectors (embeddings) that can be used for semantic search and clustering?

Question 115mediummultiple choice

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A data engineer is building a RAG application using OCI Generative AI Agents. They have documents stored in OCI Object Storage. Which resource must they create to make these documents searchable by the agent?

Question 116hardmultiple choice

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A company needs to classify customer support tickets into 20 categories. They have a labeled dataset of 50,000 examples. They want to use OCI Generative AI Embedding API to generate embeddings, then train a classifier. Which input type should they use for the embedding API when processing the training examples?

Question 117hardmultiple choice

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An organization wants to deploy a chatbot that uses a custom fine-tuned model. They have provisioned a Dedicated AI Cluster with 4 model units. During peak hours, they observe high latency and want to reduce it. What is the most cost-effective change?

Question 118mediummulti select

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A developer is creating a fine-tuning job for a Cohere Command R model using OCI Generative AI. Which TWO of the following are required when submitting the fine-tuning job?

Question 119mediummulti select

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A company is using OCI Generative AI Agents to implement a RAG system for employee onboarding. They want to ensure the agent only answers from the uploaded documents and avoids making up information. Which THREE configuration steps should they take?

Question 120hardmulti select

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A data scientist is evaluating the cost of deploying a fine-tuned model for a high-volume production application. They need low latency but are cost-sensitive. Which TWO considerations should they evaluate when choosing between on-demand (shared) and dedicated cluster pricing?

Question 121mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Question 122easymultiple choice

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Which fine-tuning technique does OCI Generative AI use to efficiently update model parameters without modifying the entire model, enabling faster training on limited data?

Question 123mediummultiple choice

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A data scientist uses OCI Generative AI Playground to test a Cohere Command R model for a summarization task. They want the summary to be concise and avoid repeating phrases. Which parameter adjustments would BEST achieve this?

Question 124hardmultiple choice

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An organization needs to deploy a custom fine-tuned model for real-time inference with consistent low latency, and they must keep the model isolated from other tenants. Which deployment option should they choose?

Question 125mediummultiple choice

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A team wants to use the Embedding API to convert product descriptions into vectors for a semantic search application. They have descriptions in English and Spanish. Which embedding model should they use?

Question 126hardmultiple choice

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A developer is using the OCI Generative AI Chat API with a system prompt to guide the assistant's behavior. They notice that after a few turns, the assistant starts ignoring the system instructions. What is the MOST likely cause?

Question 127easymultiple choice

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Which of the following is the correct format for a training dataset used in OCI Generative AI fine-tuning?

Question 128mediummultiple choice

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An administrator needs to grant a group of data scientists access to use OCI Generative AI resources in a specific compartment. Which IAM policy statement should they use?

Question 129mediummultiple choice

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A company wants to process a large batch of documents to generate summaries using OCI Generative AI. They need the most cost-effective option without compromising on summary quality. Which approach should they use?

Question 130easymultiple choice

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Which API should a developer use to send a multi-turn conversation history to an LLM, including a system message and previous user/assistant exchanges, using OCI Generative AI?

Question 131hardmultiple choice

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A machine learning engineer is fine-tuning a Cohere Command R model using T-Few. They have prepared a JSONL dataset with 500 prompt-completion pairs. After submitting the fine-tuning job, they notice the model's performance on validation data is poor. Which action is MOST likely to improve performance?

Question 132mediummultiple choice

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A developer is using the Embedding API to create embeddings for a clustering task. They want to ensure the embeddings are optimized for clustering similar documents. Which input type should they specify?

Question 133mediummulti select

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A company wants to build a RAG application using OCI Generative AI Agents. Which TWO components are required to set up the agent?

Question 134hardmulti select

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A data scientist is using the OCI Generative AI Playground to test a model for a text generation task. They want to control the output to be more focused and avoid repeating the same phrases. Which THREE parameter adjustments should they consider?

Question 135mediummulti select

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An organization needs to choose a model for a multilingual customer support chatbot that must understand and respond in five different languages. Which TWO models available in OCI Generative AI are suitable?

Question 136mediummultiple choice

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A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?