|
--- |
|
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"}) |
|
|
|
``` |
