Introduction to 0-Shot and Few-Shot
- Zero-shot learning (0-shot learning) refers to the ability of a model to correctly perform a task without having seen any examples of that task during training.
- Few-shot learning refers to the model's ability to perform tasks correctly with only a small number of examples provided. This capability is particularly crucial for efficiently deploying AI in real-world scenarios, where abundant labeled data may not always be available.
- The main difference between few-shot learning and zero-shot learning with language models like GPT-4 comes down to the number of examples provided in the prompt.
Zero-shot learning means giving
