Fine-Tuned Model

A fine-tuned model is a model that has been trained on a specific dataset to perform a specific task. Fine-tuning is a common technique used in machine learning to adapt a pre-trained model to a new task.

Fine-tuning in the context of using a large language model (LLM) is like teaching an already smart student (the AI model) about a specific subject you’re interested in. The AI model knows a lot already because it has been trained on huge amounts of general information. However, fine-tuning is needed to make it an expert in a particular area relevant to your needs.

For example, to prepare the AI for handling customer complaints, you would fine-tune it using data such as past customer service interactions, complaint resolutions, and company policies. This specialized training helps the AI understand common issues, appropriate responses, and the tone needed to address customer concerns effectively.

In summary, fine-tuning is necessary to adapt a broad-knowledge AI model to perform exceptionally well in specific tasks or topics, much like adding a specialized course to an already broad education.