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- # LayoutLMv3 base model
 
 
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  ## Model description
 
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  LayoutLMv3 is a pre-trained multimodal Transformer for Document AI with unified text and image masking. The simple unified architecture and training objectives make LayoutLMv3 a general-purpose pre-trained model. For example, LayoutLMv3 can be fine-tuned for both text-centric tasks, including form understanding, receipt understanding, and document visual question answering, and image-centric tasks such as document image classification and document layout analysis.
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- For more details, please read the [paper](https://arxiv.org/abs/2204.08387) or view the [code](https://aka.ms/layoutlmv3).
 
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  ## Citation
 
 
 
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  ```
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  @article{huang2022layoutlmv3,
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  title={LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking},
 
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+ # LayoutLMv3
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+ [Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlmv3)
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  ## Model description
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  LayoutLMv3 is a pre-trained multimodal Transformer for Document AI with unified text and image masking. The simple unified architecture and training objectives make LayoutLMv3 a general-purpose pre-trained model. For example, LayoutLMv3 can be fine-tuned for both text-centric tasks, including form understanding, receipt understanding, and document visual question answering, and image-centric tasks such as document image classification and document layout analysis.
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+ [LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking](https://arxiv.org/abs/2204.08387)
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+ Yupan Huang, Tengchao Lv, Lei Cui, Yutong Lu, Furu Wei, Preprint 2022.
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  ## Citation
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+ If you find LayoutLM useful in your research, please cite the following paper:
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  ```
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  @article{huang2022layoutlmv3,
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  title={LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking},