This project develops and evaluates machine-learning models for the automated processing of historical Greek and Latin texts. Using transformer-based architectures and existing annotated datasets, the project focuses on tasks such as linguistic tagging, metadata and orthographic extraction, metrical and structural classification, sentiment analysis, and text-to-image alignment.