| | --- |
| | language: |
| | - ar |
| | - en |
| | - es |
| | - fr |
| | - ru |
| | license: mit |
| | size_categories: |
| | - 1K<n<10K |
| | task_categories: |
| | - visual-question-answering |
| | pretty_name: XVNLI |
| | dataset_info: |
| | features: |
| | - name: label |
| | dtype: string |
| | - name: caption |
| | dtype: string |
| | - name: hypothesis |
| | dtype: string |
| | - name: caption_id |
| | dtype: string |
| | - name: pair_id |
| | dtype: string |
| | - name: flikr30k_id |
| | dtype: string |
| | - name: image |
| | struct: |
| | - name: bytes |
| | dtype: binary |
| | - name: path |
| | dtype: 'null' |
| | splits: |
| | - name: ar |
| | num_bytes: 45192381 |
| | num_examples: 1164 |
| | - name: en |
| | num_bytes: 45141859 |
| | num_examples: 1164 |
| | - name: es |
| | num_bytes: 45162738 |
| | num_examples: 1164 |
| | - name: fr |
| | num_bytes: 45161740 |
| | num_examples: 1164 |
| | - name: ru |
| | num_bytes: 45256629 |
| | num_examples: 1164 |
| | download_size: 70974300 |
| | dataset_size: 225915347 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: ar |
| | path: data/ar-* |
| | - split: en |
| | path: data/en-* |
| | - split: es |
| | path: data/es-* |
| | - split: fr |
| | path: data/fr-* |
| | - split: ru |
| | path: data/ru-* |
| | --- |
| | |
| | # XVNLI |
| |
|
| | ### This is a copy from the original repo: https://github.com/e-bug/iglue |
| |
|
| |
|
| | If you use this dataset, please cite the original authors: |
| | ```bibtex |
| | @inproceedings{bugliarello-etal-2022-iglue, |
| | title = {{IGLUE}: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages}, |
| | author = {Bugliarello, Emanuele and Liu, Fangyu and Pfeiffer, Jonas and Reddy, Siva and Elliott, Desmond and Ponti, Edoardo Maria and Vuli{\'c}, Ivan}, |
| | booktitle = {Proceedings of the 39th International Conference on Machine Learning}, |
| | pages = {2370--2392}, |
| | year = {2022}, |
| | editor = {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan}, |
| | volume = {162}, |
| | series = {Proceedings of Machine Learning Research}, |
| | month = {17--23 Jul}, |
| | publisher = {PMLR}, |
| | pdf = {https://proceedings.mlr.press/v162/bugliarello22a/bugliarello22a.pdf}, |
| | url = {https://proceedings.mlr.press/v162/bugliarello22a.html}, |
| | } |
| | ``` |
| |
|
| | ### How to read the image |
| | Due to a [bug](https://github.com/huggingface/datasets/issues/4796), the images cannot be stored as PIL.Image.Images directly but need to be converted to dataset.Images-. Hence, to load them, this additional step is required: |
| |
|
| | ```python |
| | from datasets import Image, load_dataset |
| | |
| | ds = load_dataset("floschne/xvnli", split="en") |
| | ds.map( |
| | lambda sample: { |
| | "image_t": [Image().decode_example(img) for img in sample["image"]], |
| | }, |
| | remove_columns=["image"], |
| | ).rename_columns({"image_t": "image"}) |
| | |
| | ``` |
