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Duplicate from microsoft/layoutlmv3-large
Browse filesCo-authored-by: Tengchao Lv <[email protected]>
- .gitattributes +28 -0
- README.md +33 -0
- config.json +33 -0
- merges.txt +0 -0
- preprocessor_config.json +19 -0
- pytorch_model.bin +3 -0
- tf_model.h5 +3 -0
- tokenizer_config.json +1 -0
- vocab.json +0 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language: en
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license: cc-by-nc-sa-4.0
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---
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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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@inproceedings{huang2022layoutlmv3,
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author={Yupan Huang and Tengchao Lv and Lei Cui and Yutong Lu and Furu Wei},
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title={LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking},
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booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
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year={2022}
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}
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```
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## License
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The content of this project itself is licensed under the [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/).
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Portions of the source code are based on the [transformers](https://github.com/huggingface/transformers) project.
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[Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct)
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config.json
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{
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"coordinate_size": 171,
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"eos_token_id": 2,
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"has_relative_attention_bias": true,
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"has_spatial_attention_bias": true,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"input_size": 224,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"max_2d_position_embeddings": 1024,
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"max_position_embeddings": 514,
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"max_rel_2d_pos": 256,
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"max_rel_pos": 128,
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"model_type": "layoutlmv3",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"pad_token_id": 1,
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"rel_2d_pos_bins": 64,
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"rel_pos_bins": 32,
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"second_input_size": 112,
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"shape_size": 170,
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"torch_dtype": "float32",
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"transformers_version": "4.12.5",
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"type_vocab_size": 1,
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"visual_embed": true,
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"vocab_size": 50265
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}
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merges.txt
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preprocessor_config.json
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{
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"apply_ocr": true,
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "LayoutLMv3FeatureExtractor",
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"image_mean": [
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],
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"image_std": [
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],
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"ocr_lang": null,
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"resample": 2,
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"size": 224
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}
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pytorch_model.bin
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size 1424157783
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tf_model.h5
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tokenizer_config.json
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{"errors": "replace", "unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": true, "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 512, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "roberta-large", "tokenizer_class": "LayoutLMv3Tokenizer"}
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vocab.json
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