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PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents
A Transformer-based object detection model fine-tuned for table detection in documents, trained on the PubTables1M dataset.
About Model
Table Transformer (DETR) - PubTables1M is a Transformer-based object detection model designed for table detection in unstructured documents. Fine-tuned on the PubTables1M dataset, it is based on DETR (DEtection TRansformer) and employs a "normalize before" approach, where layer normalization is applied before self- and cross-attention. This model enables accurate table extraction, making it useful for document processing tasks such as OCR, data extraction, and information retrieval.
PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents
Metadata
MIT
Microsoft
object detection
N.A.
Open
Sector Agnostic
12/03/25 06:34:55
0
Activity Overview
0
9 
0 
791
Tags
- object detection
- Transformers
- PyTorch
- safetensors
- table-transformers
- inference endpoints
License Control
MIT
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