Calibrate before use: elevating few-shot language model efficacy
In the realm of machine learning, the allure of few-shot learning beckons with a promise of efficiency and adaptability. Imagine a language model, agile enough to grasp new tasks with mere glimpses of data, where traditional models would stumble without volumes of examples. This is the art of calibration, a meticulous process akin to tuning ...