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README.md

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+---
+language: 
+  - en
+---
+
+# 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).

added_tokens.json

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+}

config.json

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+{
+  "architectures": [
+    "MarkupLMForPretraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_depth": 50,
+  "max_position_embeddings": 514,
+  "max_xpath_subs_unit_embeddings": 1024,
+  "max_xpath_tag_unit_embeddings": 256,
+  "model_type": "markuplm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float16",
+  "transformers_version": "4.10.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50267,
+  "xpath_unit_hidden_size": 32
+}

preprocessor_config.json

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+{
+  "feature_extractor_type": "MarkupLMFeatureExtractor",
+  "processor_class": "MarkupLMProcessor"
+}

pytorch_model.bin

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+size 276526721

special_tokens_map.json

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+  },
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+}

tokenizer_config.json

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