1Z0-1127-25 OCI Generative AI Service Practice Question
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?
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
✓
Upload the dataset to an OCI Object Storage bucket
The dataset must be uploaded to an OCI Object Storage bucket so the fine-tuning job can access it. The other options are either optional or not required.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Register the dataset in OCI Data Labeling
Why it's wrong here
Data Labeling is not required for fine-tuning; the dataset is already labeled as prompt/completion pairs.
- ✓
Upload the dataset to an OCI Object Storage bucket
Why this is correct
Fine-tuning jobs in OCI GenAI read training data from Object Storage.
- ✗
Deploy a dedicated AI cluster to host the base model
Why it's wrong here
A dedicated cluster is needed for inference, not for training; fine-tuning can use shared infrastructure.
- ✗
Create an OCI Functions endpoint for dataset preprocessing
Why it's wrong here
Functions are not required; the dataset can be uploaded as-is.
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