|
{ |
|
"ar": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "ar", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 107399614, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1294553, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 633001, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 59215902, |
|
"dataset_size": 109327168, |
|
"size_in_bytes": 168543070 |
|
}, |
|
"bg": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "bg", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 125973225, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1573034, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 774061, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 66117878, |
|
"dataset_size": 128320320, |
|
"size_in_bytes": 194438198 |
|
}, |
|
"de": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "de", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 84684140, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 996488, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 494604, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 55973883, |
|
"dataset_size": 86175232, |
|
"size_in_bytes": 142149115 |
|
}, |
|
"el": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "el", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 139753358, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1704785, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 841226, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 74551247, |
|
"dataset_size": 142299369, |
|
"size_in_bytes": 216850616 |
|
}, |
|
"en": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "en", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 74444026, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 875134, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 433463, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 50627367, |
|
"dataset_size": 75752623, |
|
"size_in_bytes": 126379990 |
|
}, |
|
"es": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "es", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 81383284, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 969813, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 478422, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 53677157, |
|
"dataset_size": 82831519, |
|
"size_in_bytes": 136508676 |
|
}, |
|
"fr": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "fr", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 85808779, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1029239, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 510104, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 55968680, |
|
"dataset_size": 87348122, |
|
"size_in_bytes": 143316802 |
|
}, |
|
"hi": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "hi", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 170593964, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 2073073, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 1023915, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 70908548, |
|
"dataset_size": 173690952, |
|
"size_in_bytes": 244599500 |
|
}, |
|
"ru": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "ru", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 129859615, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1603466, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 786442, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 70702606, |
|
"dataset_size": 132249523, |
|
"size_in_bytes": 202952129 |
|
}, |
|
"sw": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "sw", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 69285725, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 871651, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 429850, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 45564152, |
|
"dataset_size": 70587226, |
|
"size_in_bytes": 116151378 |
|
}, |
|
"th": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "th", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 176062892, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 2147015, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 1061160, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 77222045, |
|
"dataset_size": 179271067, |
|
"size_in_bytes": 256493112 |
|
}, |
|
"tr": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "tr", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 71637140, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 934934, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 459308, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 48509680, |
|
"dataset_size": 73031382, |
|
"size_in_bytes": 121541062 |
|
}, |
|
"ur": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "ur", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 96441486, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1416241, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 699952, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 46682785, |
|
"dataset_size": 98557679, |
|
"size_in_bytes": 145240464 |
|
}, |
|
"vi": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "vi", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 101417430, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 1190217, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 590680, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 57690058, |
|
"dataset_size": 103198327, |
|
"size_in_bytes": 160888385 |
|
}, |
|
"zh": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"hypothesis": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "zh", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 72224841, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 777929, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 384851, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 48269855, |
|
"dataset_size": 73387621, |
|
"size_in_bytes": 121657476 |
|
}, |
|
"all_languages": { |
|
"description": "XNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n", |
|
"citation": "@InProceedings{conneau2018xnli,\n author = {Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Stoyanov, Veselin},\n title = {XNLI: Evaluating Cross-lingual Sentence Representations},\n booktitle = {Proceedings of the 2018 Conference on Empirical Methods\n in Natural Language Processing},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n location = {Brussels, Belgium},\n}", |
|
"homepage": "https://www.nyu.edu/projects/bowman/xnli/", |
|
"license": "", |
|
"features": { |
|
"premise": { |
|
"languages": [ |
|
"ar", |
|
"bg", |
|
"de", |
|
"el", |
|
"en", |
|
"es", |
|
"fr", |
|
"hi", |
|
"ru", |
|
"sw", |
|
"th", |
|
"tr", |
|
"ur", |
|
"vi", |
|
"zh" |
|
], |
|
"_type": "Translation" |
|
}, |
|
"hypothesis": { |
|
"languages": [ |
|
"ar", |
|
"bg", |
|
"de", |
|
"el", |
|
"en", |
|
"es", |
|
"fr", |
|
"hi", |
|
"ru", |
|
"sw", |
|
"th", |
|
"tr", |
|
"ur", |
|
"vi", |
|
"zh" |
|
], |
|
"num_languages": 15, |
|
"_type": "TranslationVariableLanguages" |
|
}, |
|
"label": { |
|
"names": [ |
|
"entailment", |
|
"neutral", |
|
"contradiction" |
|
], |
|
"_type": "ClassLabel" |
|
} |
|
}, |
|
"builder_name": "xnli", |
|
"dataset_name": "xnli", |
|
"config_name": "all_languages", |
|
"version": { |
|
"version_str": "1.1.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 1, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 1581471691, |
|
"num_examples": 392702, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 19387432, |
|
"num_examples": 5010, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 9566179, |
|
"num_examples": 2490, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 963942271, |
|
"dataset_size": 1610425302, |
|
"size_in_bytes": 2574367573 |
|
} |
|
} |