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--- |
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license: cc-by-4.0 |
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configs: |
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- config_name: ArxivOCR |
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data_files: |
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- split: train |
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path: ArxivOCR/train-* |
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- config_name: ArxivTableCap |
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data_files: |
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- split: train |
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path: ArxivTableCap/train-* |
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- split: val |
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path: ArxivTableCap/val-* |
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- split: test |
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path: ArxivTableCap/test-* |
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- config_name: COCOtext |
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data_files: |
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- split: train |
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path: COCOtext/train-* |
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- split: val |
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path: COCOtext/val-* |
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- config_name: Open4Business |
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data_files: |
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- split: train |
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path: Open4Business/train-* |
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- split: val |
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path: Open4Business/val-* |
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- split: test |
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path: Open4Business/test-* |
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- config_name: TabFact |
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data_files: |
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- split: train |
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path: TabFact/train-* |
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- split: val |
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path: TabFact/val-* |
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- split: test |
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path: TabFact/test-* |
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- config_name: TextOCR |
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data_files: |
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- split: train |
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path: TextOCR/train-* |
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- split: val |
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path: TextOCR/val-* |
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- config_name: WikiTQ |
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data_files: |
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- split: train |
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path: WikiTQ/train-* |
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- split: val |
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path: WikiTQ/val-* |
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- split: test |
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path: WikiTQ/test-* |
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- config_name: cord-v2 |
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data_files: |
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- split: train |
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path: cord-v2/train-* |
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- split: val |
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path: cord-v2/val-* |
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- split: test |
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path: cord-v2/test-* |
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- config_name: pubtables-1m |
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data_files: |
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- split: train |
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path: pubtables-1m/train-* |
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- split: val |
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path: pubtables-1m/val-* |
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- split: test |
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path: pubtables-1m/test-* |
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dataset_info: |
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- config_name: ArxivOCR |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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dtype: string |
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- name: task_name |
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dtype: string |
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- name: query |
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sequence: string |
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- name: annotations |
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sequence: string |
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- name: image |
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dtype: image |
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- name: query_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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dtype: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: annotations_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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dtype: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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dtype: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 563398948953.968 |
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num_examples: 446016 |
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download_size: 561963351553 |
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dataset_size: 563398948953.968 |
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- config_name: ArxivTableCap |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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dtype: string |
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- name: task_name |
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dtype: string |
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- name: query |
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sequence: string |
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- name: annotations |
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sequence: string |
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- name: image |
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dtype: image |
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- name: query_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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dtype: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: annotations_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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dtype: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 5994865187.0 |
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num_examples: 71024 |
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|
- name: val |
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num_bytes: 78047974.0 |
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num_examples: 1000 |
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|
- name: test |
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num_bytes: 24057511.0 |
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num_examples: 500 |
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download_size: 6058341574 |
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dataset_size: 6096970672.0 |
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- config_name: COCOtext |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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dtype: string |
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- name: task_name |
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dtype: string |
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sequence: string |
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sequence: string |
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- name: img_id |
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dtype: string |
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- name: query_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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sequence: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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|
dtype: string |
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- name: annotations_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_attribution |
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sequence: string |
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- name: source_license |
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dtype: string |
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- name: source_url |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 66261559 |
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num_examples: 46970 |
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|
- name: val |
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num_bytes: 12498555 |
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num_examples: 8892 |
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download_size: 15280439 |
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dataset_size: 78760114 |
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- config_name: Open4Business |
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features: |
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- name: sample_id |
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|
dtype: string |
|
|
- name: dataset_name |
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|
dtype: string |
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- name: task_name |
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dtype: string |
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- name: query |
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sequence: string |
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dtype: string |
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- name: query_info |
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struct: |
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- name: notes |
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dtype: string |
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|
- name: annotations_info |
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struct: |
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- name: notes |
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|
dtype: string |
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|
- name: image_info |
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struct: |
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- name: notes |
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|
dtype: string |
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|
- name: image_sha256 |
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|
dtype: string |
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splits: |
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|
- name: train |
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num_bytes: 15054769 |
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num_examples: 27932 |
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- name: val |
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|
num_bytes: 1862001 |
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num_examples: 3492 |
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|
- name: test |
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|
num_bytes: 1869451 |
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|
num_examples: 3492 |
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|
download_size: 2997014 |
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dataset_size: 18786221 |
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- config_name: TabFact |
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|
features: |
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- name: sample_id |
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|
dtype: string |
|
|
- name: dataset_name |
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|
dtype: string |
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|
- name: task_name |
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dtype: string |
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- name: query |
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sequence: string |
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- name: img_id |
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dtype: string |
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- name: query_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: annotations_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 21877661 |
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num_examples: 39543 |
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num_bytes: 2815202 |
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num_examples: 5088 |
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- name: test |
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num_bytes: 2813402 |
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num_examples: 5085 |
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download_size: 4778068 |
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dataset_size: 27506265 |
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- config_name: TextOCR |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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dtype: string |
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- name: task_name |
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dtype: string |
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sequence: string |
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struct: |
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- name: notes |
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- name: source_license |
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- name: annotations_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_license |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 123664898 |
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num_examples: 43484 |
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- name: val |
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num_bytes: 17736515 |
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num_examples: 6232 |
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download_size: 35928078 |
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dataset_size: 141401413 |
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- config_name: WikiTQ |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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sequence: string |
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dtype: string |
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struct: |
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- name: notes |
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dtype: string |
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- name: annotations_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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num_bytes: 19880124 |
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num_examples: 6907 |
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- name: test |
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num_bytes: 6090798 |
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num_examples: 8528 |
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download_size: 2966839 |
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dataset_size: 30902022 |
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- config_name: cord-v2 |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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struct: |
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struct: |
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dtype: string |
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struct: |
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dtype: string |
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dtype: string |
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dtype: string |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 5185587863.0 |
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num_examples: 3200 |
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num_examples: 400 |
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- name: test |
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num_bytes: 654076163.0 |
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num_examples: 400 |
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download_size: 5879361638 |
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dataset_size: 6525755805.0 |
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- config_name: pubtables-1m |
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features: |
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- name: sample_id |
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dtype: string |
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- name: dataset_name |
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dtype: string |
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- name: task_name |
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dtype: string |
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sequence: string |
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- name: annotations |
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sequence: string |
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dtype: string |
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- name: query_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_license |
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struct: |
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- name: notes |
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dtype: string |
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- name: source_license |
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dtype: string |
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dtype: string |
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- name: image_info |
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struct: |
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- name: notes |
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dtype: string |
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- name: image_sha256 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 4515375098 |
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num_examples: 1371294 |
|
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- name: val |
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num_bytes: 568892238 |
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num_examples: 172887 |
|
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- name: test |
|
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num_bytes: 561231801 |
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num_examples: 170466 |
|
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download_size: 1398777256 |
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dataset_size: 5645499137 |
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--- |
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# BigDocs-7.5M |
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#### 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/) |
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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 |
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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. |
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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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