1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question
A developer is deploying a fine-tuned model using OCI Generative AI service. They want to use a custom container image for inference. Which statement is true?
⚠ Common exam trap
Test-takers frequently confuse the scope of custom container support, assuming it is limited to OCI Data Science or only for training, when in fact OCI Generative AI explicitly supports custom containers for inference via dedicated AI clusters.
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
✓
You can upload a container image to OCI Container Registry and reference it when creating a dedicated AI cluster.
OCI Generative AI service allows you to bring your own custom container image for inference by uploading it to OCI Container Registry (OCIR) and referencing it when creating a dedicated AI cluster. This enables you to deploy fine-tuned models with custom inference logic, dependencies, or frameworks that are not available in the built-in serving containers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Custom containers are only supported with OCI Data Science, not Generative AI.
Why it's wrong here
Incorrect: OCI Generative AI service also supports custom containers.
- ✓
You can upload a container image to OCI Container Registry and reference it when creating a dedicated AI cluster.
Why this is correct
Correct: This is the documented approach for using custom inference containers.
- ✗
Custom containers are supported only for fine-tuning jobs, not inference.
Why it's wrong here
Incorrect: Custom containers can be used for inference as well.
- ✗
Custom containers are not supported; only built-in models are available.
Why it's wrong here
Incorrect: The service allows custom containers for fine-tuned models.
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