About
This skill streamlines the transfer learning workflow by automating model adaptation, data validation, and performance optimization. It enables developers to quickly repurpose state-of-the-art models—such as ResNet for computer vision or BERT for natural language processing—for new applications by generating framework-specific code in PyTorch or TensorFlow. By handling complex preprocessing, architectural modifications, and performance reporting, it significantly reduces the time and resources required to deploy high-performing models on specialized datasets.