Fine-tuning involves modifying a pre-trained language model by training it on a specific task using supervised learning.

Rather than spelling out every procedure, a base program such as an image recognizer or categorizer is built, and then trained by feeding it large amounts of data labeled by humans until it can recognize patterns in the data on its own. We teach the program what success looks like, and it learns to copy us.

Setting this up involves training your chatbot with examples of possible user interactions, including questions or statements and how the chatbot should respond. The more examples you provide, the better your chatbot will become at understanding and responding to users. This process, known as training the model, is pivotal as it directly affects th