This report details the development of an AI-based model for the automatic classification of abnormalities in wireless capsule endoscopy (WCE) images. We leverage Vision Transformers (ViTs) for enhanced performance and compare our results against established benchmarks. Various preprocessing techniques were explored to optimize image quality and model accuracy.