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Deploying and Managing Generative AI on OCIhardMultiple SelectObjective-mapped

1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question

Which THREE steps are required to deploy a custom generative AI model using OCI Data Science Model Deployment?

⚠ Common exam trap

Test-takers frequently confuse the OCI Generative AI service's managed model lifecycle (fine-tuning and registration) with the custom model deployment workflow in OCI Data Science, leading candidates to incorrectly select steps that belong to the managed service rather than the custom deployment pipeline.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Create a model artifact (e.g., pickle, ONNX) with inference code

Deploying a custom generative AI model via OCI Data Science Model Deployment requires packaging the model and its inference code into a standardized artifact format (e.g., pickle, ONNX). This artifact is the core input that the deployment runtime loads to serve predictions, making it an essential step in the workflow.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Fine-tune the model using OCI Generative AI service

    Why it's wrong here

    Fine-tuning is a prior step; deployment steps assume model is ready.

  • Create a model artifact (e.g., pickle, ONNX) with inference code

    Why this is correct

    Model must be packaged with dependencies for serving.

  • Register the model in OCI Generative AI service

    Why it's wrong here

    Generative AI service is separate; custom models are deployed via Data Science.

  • Upload the model artifact to an OCI Object Storage bucket

    Why this is correct

    Model Deployment loads the artifact from Object Storage.

  • Create a model deployment using the OCI Data Science Model Deployment service

    Why this is correct

    This creates the endpoint.

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