1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question
A data scientist needs to fine-tune a model on OCI Generative AI. Which of the following is a required parameter in the fine-tuning request?
⚠ Common exam trap
Oracle often tests the 'All of the above' pattern when each individual option is factually correct but candidates incorrectly assume only one is required, missing the comprehensive nature of the fine-tuning request.
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
✓
All of the above
In OCI Generative AI, the fine-tuning request requires all three parameters: hyperparameters (to define training behavior like learning rate and epochs), model_name (to specify the base model being fine-tuned), and dataset_type (to indicate the format of the training data, such as 'TEXT' or 'MULTI_TURN'). Therefore, 'All of the above' is correct because each listed option is a mandatory field in the fine-tuning API call.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
hyperparameters
Why it's wrong here
Hyperparameters are required, but not the only required parameter.
- ✗
model_name
Why it's wrong here
The base model name is required, but not the only required parameter.
- ✗
dataset_type
Why it's wrong here
The dataset type is required, but not the only required parameter.
- ✓
All of the above
Why this is correct
All three (model_name, dataset_type, hyperparameters) are required for a fine-tuning request.
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