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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 Metadata

MIT

Microsoft

object detection

N.A.

Open

Sector Agnostic

12/03/25 06:34:55

0

Activity Overview Activity Overview

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Tags Tags

  • object detection
  • Transformers
  • PyTorch
  • safetensors
  • table-transformers
  • inference endpoints

License Control License Control

MIT

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