SetFit and SBERT: Zero-Shot Classification with Synthetic Data Sets - Part 47

Learn how to leverage SetFit and SBERT for zero-shot classification through a 26-minute technical video that explores creating synthetic datasets for training. Discover the innovative approach of generating synthetic examples that mirror classification tasks to train SetFit models when labeled data is scarce or unavailable. Master techniques for both zero-shot classification with synthetic data and boosting few-shot classification performance through synthetic example augmentation. Explore practical applications of SetFit, originally designed for few-shot learning, in scenarios with limited or no labeled training data.