Zero-shot saves weeks of labeling work.
How It Works:
Use prompt templates or label descriptions at runtime, route inputs through the model?s classification API, and fall back to human review for low-confidence cases.
Key Benefits:
Real-World Use Cases:
Calibrate on a small validation set and adjust for precision vs. recall.
Yes-hybrid prompts often improve accuracy.