
# MarkupLM

**Multimodal (text +markup language) pre-training for [Document AI](https://www.microsoft.com/en-us/research/project/document-ai/)**

## Introduction

MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extraction tasks, such as webpage QA and webpage information extraction. MarkupLM archives the SOTA results on multiple datasets. For more details, please refer to our paper:

[MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding](https://arxiv.org/abs/2110.08518)  Junlong Li, Yiheng Xu, Lei Cui, Furu Wei, ACL 2022

## Usage

We refer to the [docs](https://huggingface.co/docs/transformers/main/en/model_doc/markuplm) and [demo notebooks](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/MarkupLM).
{"language": ["en"]}
transformers pytorch markuplm en arxiv:2110.08518 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #markuplm #en #arxiv-2110.08518 #endpoints_compatible #has_space #region-us 


# MarkupLM

Multimodal (text +markup language) pre-training for Document AI

## Introduction

MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extraction tasks, such as webpage QA and webpage information extraction. MarkupLM archives the SOTA results on multiple datasets. For more details, please refer to our paper:

MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding  Junlong Li, Yiheng Xu, Lei Cui, Furu Wei, ACL 2022

## Usage

We refer to the docs and demo notebooks.
# MarkupLM

Multimodal (text +markup language) pre-training for Document AI ## Introduction

MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extraction tasks, such as webpage QA and webpage information extraction. MarkupLM archives the SOTA results on multiple datasets. For more details, please refer to our paper:

MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding  Junlong Li, Yiheng Xu, Lei Cui, Furu Wei, ACL 2022 ## Usage

We refer to the docs and demo notebooks.
TAGS
#transformers #pytorch #markuplm #en #arxiv-2110.08518 #endpoints_compatible #has_space #region-us 
 # MarkupLM

Multimodal (text +markup language) pre-training for Document AI ## Introduction

MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extraction tasks, such as webpage QA and webpage information extraction. MarkupLM archives the SOTA results on multiple datasets. For more details, please refer to our paper:

MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding  Junlong Li, Yiheng Xu, Lei Cui, Furu Wei, ACL 2022 ## Usage

We refer to the docs and demo notebooks.
passage: TAGS
#transformers #pytorch #markuplm #en #arxiv-2110.08518 #endpoints_compatible #has_space #region-us 
# MarkupLM

Multimodal (text +markup language) pre-training for Document AI## Introduction

MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extraction tasks, such as webpage QA and webpage information extraction. MarkupLM archives the SOTA results on multiple datasets. For more details, please refer to our paper:

MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding  Junlong Li, Yiheng Xu, Lei Cui, Furu Wei, ACL 2022## Usage

We refer to the docs and demo notebooks.