microsoft / layoutlm-base-cased

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Introduction of layoutlm-base-cased

Model Details of layoutlm-base-cased

LayoutLM

Multimodal (text + layout/format + image) pre-training for document AI

Microsoft Document AI | GitHub

Model description

LayoutLM is a simple but effective pre-training method of text and layout for document image understanding and information extraction tasks, such as form understanding and receipt understanding. LayoutLM archives the SOTA results on multiple datasets. For more details, please refer to our paper:

LayoutLM: Pre-training of Text and Layout for Document Image Understanding Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, KDD 2020

Different Tokenizer

Note that LayoutLM-Cased requires a different tokenizer, based on RobertaTokenizer. You can initialize it as follows:

from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('microsoft/layoutlm-base-cased') 
Citation

If you find LayoutLM useful in your research, please cite the following paper:

@misc{xu2019layoutlm,
    title={LayoutLM: Pre-training of Text and Layout for Document Image Understanding},
    author={Yiheng Xu and Minghao Li and Lei Cui and Shaohan Huang and Furu Wei and Ming Zhou},
    year={2019},
    eprint={1912.13318},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

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12.8K
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layoutlm-base-cased is an open source model from GitHub that offers a free installation service, and any user can find layoutlm-base-cased on GitHub to install. At the same time, huggingface.co provides the effect of layoutlm-base-cased install, users can directly use layoutlm-base-cased installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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