Introduction
Language models are pretrained models that provide you with a great starting point. By using one of the available base or foundation models, you can save time and effort as you need less data to train a model for your specific use case.
Imagine you're a developer working for a travel agency. When customers use your chat application to get help with their travel-related questions, you want the responses to be in a specific format and style. Your company has a specific tone of voice that resonates with your client base. The marketing department finds it important that the chat application is aligned with your company's tone of voice too.
There are various strategies to optimize the model's behavior and the performance of your chat application. One strategy is to fine-tune a language model, which you can then integrate with your chat application. The benefit of fine-tuning over training your own language model, is that you need less time, compute resources, and data to customize the model to your needs.
In this module, you learn how to fine-tune a base model from the model catalog in the Azure AI Foundry portal, that you can then integrate in a chat application.