Table Transformer (TATR) is a deep learning-based object detection model for extracting tables from unstructured documents. It uses a DETR-style architecture to detect and parse table structures from images and PDFs. The repository includes the PubTables-1M dataset with over 1 million tables, the GriTS evaluation metric for table structure recognition, and pre-trained models for table detection, structure recognition, and functional analysis.