Fine-Tuning Generative Models for Specific Tasks
In our narrative with StyleSprint, we described using a pre-trained generative AI model for creating engaging product descriptions. While this model showed adeptness in generating diverse content, StyleSprint’s evolving needs require a shift in focus. The new challenge is not just about producing content but also about engaging in specific, task-oriented interactions such as automatically answering customer’s specific questions about the products described.
In this chapter, we introduce the concept of fine-tuning, a vital step in adapting a pre-trained model to perform specific downstream tasks. For StyleSprint, this means transforming the model from a versatile content generator to a specialized tool capable of providing accurate and detailed responses to customer questions.
We will explore and define a range of scalable fine-tuning techniques, comparing them with other approaches such as in-context learning. We...
