Fine-tuning is the process of training a base language model on a dataset to perform better in a specific domain or for a target use case. By leveraging the foundational knowledge already embedded in the model, fine-tuning allows the model to specialize in tasks like customer support automation, medical text classification, or legal document summarization.This approach significantly reduces the time and resources needed compared to training a model scratch, while still delivering high accuracy and relevance.
To meet this growing demand, Model Fine-tuning is built by FPT Smart Cloud to be user-friendly, enabling AI customization through a simple interface on the FPT AI Factory Portal. Users can upload their dataset, configure training hyperparameters, and set up infrastructure - all within a few clicks.

Thanks to this streamlined approach, Model Fine-tuning empowers organizations to unlock the full potential of AI, delivering smarter, faster, and more accurate solutions tailored to their unique business needs.