Government Of India
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Table Transformer (TATR) - Table Structure Recognition
A Transformer-based object detection model pre-trained for table structure recognition, including row and column detection, using the PubTables1M and FinTabNet datasets.
About Model
Table Transformer (TATR) - Table Structure Recognition is a Transformer-based object detection model trained on the PubTables1M and FinTabNet datasets. It is designed to detect and recognize table structures, such as rows, columns, and table boundaries, in unstructured documents. Based on DETR (DEtection TRansformer), the model employs a "normalize before" approach, applying layer normalization before self- and cross-attention. This model is particularly useful for document analysis, table parsing, and structured data extraction from scanned PDFs and images.
Table Transformer (TATR) - Table Structure Recognition
Metadata
MIT
Microsoft
object detection
N.A.
Open
Sector Agnostic
12/03/25 06:34:57
0
Activity Overview
0
4 
462 
0
Tags
- object detection
- Transformers
- PyTorch
- safetensors
- table-transformers
- inference endpoints
License Control
MIT
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