OCI Generative AI Service

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

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?

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?

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?

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?

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

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?

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

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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)

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?

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?

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?

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.)

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?

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?

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?

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

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?

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?

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?

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?

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

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?

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?

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

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?

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?

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?

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?

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?

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?

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?

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)

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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

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?

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?

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

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?

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?

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?

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

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?

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?

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?

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?

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?

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?

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.)

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?

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.)

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

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?

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?

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?

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?

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

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)

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

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?

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

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?

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?

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

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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

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?

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.)

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?

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?

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?

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?

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

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?

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?

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?

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?

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?

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

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?

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?

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

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?

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?

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?

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?

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?