Fine-tuning vs.Prompting: Two Types of Usage Derived from Different Expectations for LLMs
Summary This video introduces two different expectations about large language models: Fine-tuning and Prompting, corresponding to different techniques. Fine-tuning uses training data to fine-tune the model for a specific task; Prompting provides the model with instructions described in human language, with the expectation that the model will correctly understand the instructions and generate the correct answers. Both approaches have advantages and disadvantages. In this part, we discuss further about instruction learning and in-context learning in natural language processing....