ExitVCEDump1Z0-1127-25Oracle Cloud Infrastructure 2025 Generative AI Professional
Question 7 of 14
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Q7Single choice
Which statement is true about Fine-tuning and Parameter-Efficient Fine-Tuning (PEFT)?
A
Fine-tuning requires training the entire model on new data, often leading to substantial computational costs, whereas PEFT involves updating only a small subset of parameters, minimizing computational requirements and data needs.
B
PEFT requires replacing the entire model architecture with a new one designed specifically for the new task, making it significantly more data-intensive than Fine-tuning.
C
Both Fine-tuning and PEFT require the model to be trained from scratch on new data, making them equally data and computationally intensive.
D
Fine-tuning and PEFT do not involve model modification; they differ only in the type of data used for training, with Fine-tuning requiring labeled data and PEFT using unlabeled data.