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Update app.py
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app.py
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@@ -129,7 +129,7 @@ description = "Fine-tuned Microsoft's LayoutLMv3 on WildReceipt Dataset to parse
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article="<b>References</b><br>[1] Y. Xu et al., βLayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking.β 2022. <a href='https://arxiv.org/abs/2204.08387'>Paper Link</a><br>[2] <a href='https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3'>LayoutLMv3 training and inference</a><br>[3] Hongbin Sun, Zhanghui Kuang, Xiaoyu Yue, Chenhao Lin, and Wayne Zhang. 2021. Spatial Dual-Modality Graph Reasoning for Key Information Extraction. arXiv. DOI:https://doi.org/10.48550/ARXIV.2103.14470 <a href='https://doi.org/10.48550/ARXIV.2103.14470'>Paper Link</a>"
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examples =[['example1.png'],['example2.png'],['example3.png']]
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css = """.output_image, .input_image {height: 600px !important}"""
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article="<b>References</b><br>[1] Y. Xu et al., βLayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking.β 2022. <a href='https://arxiv.org/abs/2204.08387'>Paper Link</a><br>[2] <a href='https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LayoutLMv3'>LayoutLMv3 training and inference</a><br>[3] Hongbin Sun, Zhanghui Kuang, Xiaoyu Yue, Chenhao Lin, and Wayne Zhang. 2021. Spatial Dual-Modality Graph Reasoning for Key Information Extraction. arXiv. DOI:https://doi.org/10.48550/ARXIV.2103.14470 <a href='https://doi.org/10.48550/ARXIV.2103.14470'>Paper Link</a>"
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examples =[['example1.png'],['example2.png'],['example3.png'],['inv2.jpg']]
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css = """.output_image, .input_image {height: 600px !important}"""
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