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Deploying and Managing Generative AI on OCImediumMultiple SelectObjective-mapped

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

Which TWO factors should be considered when selecting a base model for fine-tuning on OCI Generative AI service?

⚠ Common exam trap

Oracle often tests the misconception that technical details like training framework or dataset size are relevant, when in fact the exam focuses on operational and legal factors (size/license) that directly affect deployment and compliance in OCI's managed service.

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

The model's size and number of parameters

When selecting a base model for fine-tuning on OCI Generative AI service, the model's size and number of parameters (B) directly impact computational cost, training time, and the model's capacity to learn from your dataset. The model's license and terms of use (C) are critical because commercial use, redistribution, and fine-tuning rights vary per model (e.g., Llama 2 vs. GPT-based models), and violating these can lead to legal or compliance issues.

Answer analysis

Option-by-option breakdown

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

  • The model's training dataset size

    Why it's wrong here

    Base model is pre-trained; you add your own dataset for fine-tuning.

  • The model's size and number of parameters

    Why this is correct

    Larger models consume more resources and cost more to serve.

  • The model's license and terms of use

    Why this is correct

    Must comply with licensing for commercial use.

  • The model's training framework (PyTorch vs TensorFlow)

    Why it's wrong here

    Fine-tuning uses OCI managed infrastructure; framework is abstracted.

  • The model's built-in features like content filtering

    Why it's wrong here

    Content filtering can be added post-deployment; not a base model selection factor.

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This 1Z0-1127-25 practice question is part of Courseiva's free Oracle certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 1Z0-1127-25 exam.