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license: mit |
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datasets: |
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- bsmock/pubtables-1m |
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- bsmock/fintabnet.c |
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tags: |
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- table structure recognition |
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- table extraction |
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--- |
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# Model Card for TATR-v1.1-All |
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This repo contains the model weights for TATR (Table Transformer) v1.1, trained on the PubTables-1M and FinTabNet.c datasets, using the training details in the paper: ["Aligning benchmark datasets for table structure recognition"](https://arxiv.org/abs/2303.00716). |
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These model weights are intended to be used with [the Microsoft implementation of Table Transformer (TATR)](https://github.com/microsoft/table-transformer). |
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This model was trained to work best on tightly cropped table images (5 pixels or less). |
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Images with significant padding included around the table were not included in the training, and so the model may not perform well on these at inference. |
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Use a table detection model to detect and tightly crop the table prior to passing to this model. |
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Model weights that can be loaded into the Hugging Face implementation of TATR are coming soon. |
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FinTabNet.c will be officially released soon. |
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Please see [our GitHub repo](https://github.com/microsoft/table-transformer) for a script to create FinTabNet.c from the [original FinTabNet dataset](https://developer.ibm.com/exchanges/data/all/fintabnet/). |
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## Model Details |
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### Model Description |
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- **Developed by:** Brandon Smock and Rohith Pesala, while at Microsoft |
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- **License:** MIT |
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- **Finetuned from model:** DETR ResNet-18 |
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### Model Sources |
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Please see the following for more details: |
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- **Repository:** ["https://github.com/microsoft/table-transformer"](https://github.com/microsoft/table-transformer) |
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- **Paper:** ["Aligning benchmark datasets for table structure recognition"](https://arxiv.org/abs/2303.00716) |
