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  🌐 [Homepage](https://bigdocs.github.io) | 📖 [arXiv](https://arxiv.org/pdf/2412.04626)
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- ## 🔔 News
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-
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- - **[2025-04-23]: Initial release of the BigDocs-7.5M data.**
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-
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  ## Guide on Data Loading
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  Some parts of BigDocs-7.5M are distributed without their "image" column, and instead have an "img_id" column. The file `get_bigdocs_75m.py`, part of this repository, provides tooling to substitutes such images back in.
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  ```python
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  from get_bigdocs_75m import get_bigdocs_75m
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  cocotext = get_bigdocs_75m("COCOtext", user_local_path=".../train2014")
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  pubtables1m = get_bigdocs_75m("pubtables-1m", user_local_path=".../PubTables-1M-Detection/images")
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  textocr = get_bigdocs_75m("TextOCR", user_local_path=".../train")
 
 
 
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  ```
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  When specified, `user_local_path` must point to one of the third-party datasets listed below.
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  - COCOtext: http://images.cocodataset.org/zips/train2014.zip
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  - pubtables-1m: https://www.microsoft.com/en-us/research/publication/pubtables-1m
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  - TextOCR: https://dl.fbaipublicfiles.com/textvqa/images/train_val_images.zip
 
 
 
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- See the docstring in `get_bigdocs_75m.py` for more details.
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  ## Licensing
 
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  🌐 [Homepage](https://bigdocs.github.io) | 📖 [arXiv](https://arxiv.org/pdf/2412.04626)
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  ## Guide on Data Loading
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  Some parts of BigDocs-7.5M are distributed without their "image" column, and instead have an "img_id" column. The file `get_bigdocs_75m.py`, part of this repository, provides tooling to substitutes such images back in.
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  ```python
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  from get_bigdocs_75m import get_bigdocs_75m
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+ arxivocr = get_bigdocs_75m("ArxivOCR")
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+ arxivtablecap = get_bigdocs_75m("ArxivTableCap")
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  cocotext = get_bigdocs_75m("COCOtext", user_local_path=".../train2014")
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  pubtables1m = get_bigdocs_75m("pubtables-1m", user_local_path=".../PubTables-1M-Detection/images")
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  textocr = get_bigdocs_75m("TextOCR", user_local_path=".../train")
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+ tabfact = get_bigdocs_75m("TabFact", user_local_path=".../Table-Fact-Checking")
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+ open4business = get_bigdocs_75m("Open4Business", user_local_path=".../Open4Business")
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+ wikitq = get_bigdocs_75m("WikiTQ", user_local_path=".../WikiTableQuestions")
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  ```
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  When specified, `user_local_path` must point to one of the third-party datasets listed below.
 
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  - COCOtext: http://images.cocodataset.org/zips/train2014.zip
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  - pubtables-1m: https://www.microsoft.com/en-us/research/publication/pubtables-1m
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  - TextOCR: https://dl.fbaipublicfiles.com/textvqa/images/train_val_images.zip
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+ - TabFact: https://github.com/wenhuchen/Table-Fact-Checking
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+ - Open4Business: https://github.com/amanpreet692/Open4Business
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+ - WikiTQ: https://github.com/ppasupat/WikiTableQuestions
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+ You may specify `num_proc` as you would for `datasets.map`. See the docstring in `get_bigdocs_75m.py` for more details.
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  ## Licensing