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---
license: cc-by-4.0
configs:
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data_files:
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path: Open4Business/val-*
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data_files:
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path: TabFact/val-*
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path: TabFact/test-*
- config_name: TextOCR
data_files:
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- config_name: WikiTQ
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---
# BigDocs-7.5M
#### Training data for the paper: [BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks](https://huggingface.co/datasets/ServiceNow/BigDocs-Bench-Collections/)
🌐 [Homepage](https://bigdocs.github.io) | 📖 [arXiv](https://arxiv.org/pdf/2412.04626)
## Guide on Data Loading
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.
```python
from get_bigdocs_75m import get_bigdocs_75m
arxivocr = get_bigdocs_75m("ArxivOCR")
arxivtablecap = get_bigdocs_75m("ArxivTableCap")
cocotext = get_bigdocs_75m("COCOtext", user_local_path=".../train2014")
pubtables1m = get_bigdocs_75m("pubtables-1m", user_local_path=".../PubTables-1M-Detection/images")
textocr = get_bigdocs_75m("TextOCR", user_local_path=".../train")
tabfact = get_bigdocs_75m("TabFact", user_local_path=".../Table-Fact-Checking")
open4business = get_bigdocs_75m("Open4Business", user_local_path=".../Open4Business")
wikitq = get_bigdocs_75m("WikiTQ", user_local_path=".../WikiTableQuestions")
```
When specified, `user_local_path` must point to one of the third-party datasets listed below.
- COCOtext: http://images.cocodataset.org/zips/train2014.zip
- pubtables-1m: https://www.microsoft.com/en-us/research/publication/pubtables-1m
- TextOCR: https://dl.fbaipublicfiles.com/textvqa/images/train_val_images.zip
- TabFact: https://github.com/wenhuchen/Table-Fact-Checking
- Open4Business: https://github.com/amanpreet692/Open4Business
- WikiTQ: https://github.com/ppasupat/WikiTableQuestions
You may specify `num_proc` as you would for `datasets.map`. See the docstring in `get_bigdocs_75m.py` for more details.
## Licensing
The part of this repository generated by us is Copyright ServiceNow 2024 and licensed under the [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) license.
Multiple datasets, documents, and tools were involved in the generation of BigDocs-Bench. We document these dependencies on a per-sample basis through the `query_info`, `annotation_info` and `image_info` fields, respectively documenting the `query`, `annotations` and `image` fields of our datasets.
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