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LayoutLMv2 - Multimodal Document Understanding

An improved multimodal Transformer model for document AI, integrating text, layout, and image pre-training for enhanced document understanding tasks such as form recognition, document classification, and visual question answering.

About Model

LayoutLMv2 is an advanced version of the LayoutLM model, designed for document AI applications by integrating text, layout, and image information into a unified multimodal framework. This model enhances document understanding through pre-training tasks that improve interaction among different modalities, leading to superior performance in visually rich document processing. It achieves state-of-the-art results on various benchmark tasks, including form recognition, receipt and invoice understanding, and document-based question answering. Built for tasks requiring OCR and document layout comprehension, LayoutLMv2 is widely applicable in automated document processing, financial data extraction, and AI-driven document analysis.

LayoutLMv2 - Multimodal Document Understanding

Metadata Metadata

Attribution-Non-Commercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou

Transformers

Other

Open

Sector Agnostic

20/08/25 11:45:33

0

Activity Overview Activity Overview

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  • Redirect 9
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Tags Tags

  • PyTorch
  • Transformers
  • ONNX
  • English
  • safetensors
  • inference endpoints
  • tensorflow
  • layoutlmv3

License Control License Control

Attribution-Non-Commercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

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