Comprehensive and Detailed In-Depth Explanation=
T-Few is ideal for smaller datasets (e.g., a few thousand samples) where full fine-tuning risks overfitting and is computationally wasteful-Option C is correct. Option A (semantic understanding) is too vague-dataset size matters more. Option B (dedicated cluster) isn't a condition for T-Few. Option D (large datasets) favors Vanilla fine-tuning. T-Few excels in low-data scenarios.
OCI 2025 Generative AI documentation likely specifies T-Few use cases under fine-tuning guidelines.