
# Dataset Card for "xnli"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://www.nyu.edu/projects/bowman/xnli/](https://www.nyu.edu/projects/bowman/xnli/)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 7.74 GB
- **Size of the generated dataset:** 3.23 GB
- **Total amount of disk used:** 10.97 GB

### Dataset Summary

XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels).

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### all_languages

- **Size of downloaded dataset files:** 483.96 MB
- **Size of the generated dataset:** 1.61 GB
- **Total amount of disk used:** 2.09 GB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{
    "hypothesis": "{\"language\": [\"ar\", \"bg\", \"de\", \"el\", \"en\", \"es\", \"fr\", \"hi\", \"ru\", \"sw\", \"th\", \"tr\", \"ur\", \"vi\", \"zh\"], \"translation\": [\"احد اع...",
    "label": 0,
    "premise": "{\"ar\": \"واحدة من رقابنا ستقوم بتنفيذ تعليماتك كلها بكل دقة\", \"bg\": \"един от нашите номера ще ви даде инструкции .\", \"de\": \"Eine ..."
}
```

#### ar

- **Size of downloaded dataset files:** 483.96 MB
- **Size of the generated dataset:** 109.32 MB
- **Total amount of disk used:** 593.29 MB

An example of 'validation' looks as follows.
```
{
    "hypothesis": "اتصل بأمه حالما أوصلته حافلة المدرسية.",
    "label": 1,
    "premise": "وقال، ماما، لقد عدت للمنزل."
}
```

#### bg

- **Size of downloaded dataset files:** 483.96 MB
- **Size of the generated dataset:** 128.32 MB
- **Total amount of disk used:** 612.28 MB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{
    "hypothesis": "\"губиш нещата на следното ниво , ако хората си припомнят .\"...",
    "label": 0,
    "premise": "\"по време на сезона и предполагам , че на твоето ниво ще ги загубиш на следващото ниво , ако те решат да си припомнят отбора на ..."
}
```

#### de

- **Size of downloaded dataset files:** 483.96 MB
- **Size of the generated dataset:** 86.17 MB
- **Total amount of disk used:** 570.14 MB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{
    "hypothesis": "Man verliert die Dinge auf die folgende Ebene , wenn sich die Leute erinnern .",
    "label": 0,
    "premise": "\"Du weißt , während der Saison und ich schätze , auf deiner Ebene verlierst du sie auf die nächste Ebene , wenn sie sich entschl..."
}
```

#### el

- **Size of downloaded dataset files:** 483.96 MB
- **Size of the generated dataset:** 142.30 MB
- **Total amount of disk used:** 626.26 MB

An example of 'validation' looks as follows.
```
This example was too long and was cropped:

{
    "hypothesis": "\"Τηλεφώνησε στη μαμά του μόλις το σχολικό λεωφορείο τον άφησε.\"...",
    "label": 1,
    "premise": "Και είπε, Μαμά, έφτασα στο σπίτι."
}
```

### Data Fields

The data fields are the same among all splits.

#### all_languages
- `premise`: a multilingual `string` variable, with possible languages including `ar`, `bg`, `de`, `el`, `en`.
- `hypothesis`: a multilingual `string` variable, with possible languages including `ar`, `bg`, `de`, `el`, `en`.
- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).

#### ar
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).

#### bg
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).

#### de
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).

#### el
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).

### Data Splits

|    name     |train |validation|test|
|-------------|-----:|---------:|---:|
|all_languages|392702|      2490|5010|
|ar           |392702|      2490|5010|
|bg           |392702|      2490|5010|
|de           |392702|      2490|5010|
|el           |392702|      2490|5010|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@InProceedings{conneau2018xnli,
  author = {Conneau, Alexis
                 and Rinott, Ruty
                 and Lample, Guillaume
                 and Williams, Adina
                 and Bowman, Samuel R.
                 and Schwenk, Holger
                 and Stoyanov, Veselin},
  title = {XNLI: Evaluating Cross-lingual Sentence Representations},
  booktitle = {Proceedings of the 2018 Conference on Empirical Methods
               in Natural Language Processing},
  year = {2018},
  publisher = {Association for Computational Linguistics},
  location = {Brussels, Belgium},
}
```


### Contributions

Thanks to [@lewtun](https://github.com/lewtun), [@mariamabarham](https://github.com/mariamabarham), [@thomwolf](https://github.com/thomwolf), [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.
language:en region:us
{"language": ["en"], "paperswithcode_id": "xnli", "pretty_name": "Cross-lingual Natural Language Inference", "dataset_info": [{"config_name": "nllb-200-distilled-600M", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 851225, "num_examples": 5010}, {"name": "bg", "num_bytes": 860275, "num_examples": 5010}, {"name": "de", "num_bytes": 852016, "num_examples": 5010}, {"name": "el", "num_bytes": 852043, "num_examples": 5010}, {"name": "es", "num_bytes": 862194, "num_examples": 5010}, {"name": "fr", "num_bytes": 861464, "num_examples": 5010}, {"name": "hi", "num_bytes": 839337, "num_examples": 5010}, {"name": "ru", "num_bytes": 860117, "num_examples": 5010}, {"name": "sw", "num_bytes": 829257, "num_examples": 5010}, {"name": "th", "num_bytes": 845834, "num_examples": 5010}, {"name": "tr", "num_bytes": 840611, "num_examples": 5010}, {"name": "ur", "num_bytes": 829009, "num_examples": 5010}, {"name": "vi", "num_bytes": 846643, "num_examples": 5010}, {"name": "zh", "num_bytes": 851646, "num_examples": 5010}], "download_size": 11040341, "dataset_size": 11881671}, {"config_name": "nllb-200-distilled-1.3B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 851205, "num_examples": 5010}, {"name": "bg", "num_bytes": 857938, "num_examples": 5010}, {"name": "de", "num_bytes": 849800, "num_examples": 5010}, {"name": "el", "num_bytes": 849820, "num_examples": 5010}, {"name": "es", "num_bytes": 860984, "num_examples": 5010}, {"name": "fr", "num_bytes": 862545, "num_examples": 5010}, {"name": "hi", "num_bytes": 848151, "num_examples": 5010}, {"name": "ru", "num_bytes": 858069, "num_examples": 5010}, {"name": "sw", "num_bytes": 830347, "num_examples": 5010}, {"name": "th", "num_bytes": 841814, "num_examples": 5010}, {"name": "tr", "num_bytes": 840738, "num_examples": 5010}, {"name": "ur", "num_bytes": 828996, "num_examples": 5010}, {"name": "vi", "num_bytes": 848990, "num_examples": 5010}, {"name": "zh", "num_bytes": 855461, "num_examples": 5010}], "download_size": 11043528, "dataset_size": 11884858}, {"config_name": "nllb-200-1.3B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 855256, "num_examples": 5010}, {"name": "bg", "num_bytes": 861195, "num_examples": 5010}, {"name": "de", "num_bytes": 854679, "num_examples": 5010}, {"name": "el", "num_bytes": 852766, "num_examples": 5010}, {"name": "es", "num_bytes": 863689, "num_examples": 5010}, {"name": "fr", "num_bytes": 868360, "num_examples": 5010}, {"name": "hi", "num_bytes": 846414, "num_examples": 5010}, {"name": "ru", "num_bytes": 865308, "num_examples": 5010}, {"name": "sw", "num_bytes": 830998, "num_examples": 5010}, {"name": "th", "num_bytes": 846171, "num_examples": 5010}, {"name": "tr", "num_bytes": 845907, "num_examples": 5010}, {"name": "ur", "num_bytes": 838279, "num_examples": 5010}, {"name": "vi", "num_bytes": 848249, "num_examples": 5010}, {"name": "zh", "num_bytes": 846116, "num_examples": 5010}], "download_size": 11082057, "dataset_size": 11923387}, {"config_name": "nllb-200-3.3B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 863302, "num_examples": 5010}, {"name": "bg", "num_bytes": 863677, "num_examples": 5010}, {"name": "de", "num_bytes": 857147, "num_examples": 5010}, {"name": "el", "num_bytes": 856383, "num_examples": 5010}, {"name": "es", "num_bytes": 866137, "num_examples": 5010}, {"name": "fr", "num_bytes": 871853, "num_examples": 5010}, {"name": "hi", "num_bytes": 857305, "num_examples": 5010}, {"name": "ru", "num_bytes": 869523, "num_examples": 5010}, {"name": "sw", "num_bytes": 839567, "num_examples": 5010}, {"name": "th", "num_bytes": 850312, "num_examples": 5010}, {"name": "tr", "num_bytes": 851657, "num_examples": 5010}, {"name": "ur", "num_bytes": 832903, "num_examples": 5010}, {"name": "vi", "num_bytes": 856479, "num_examples": 5010}, {"name": "zh", "num_bytes": 853093, "num_examples": 5010}], "download_size": 11148008, "dataset_size": 11989338}, {"config_name": "xglm-564M", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 789329, "num_examples": 5010}, {"name": "bg", "num_bytes": 846003, "num_examples": 5010}, {"name": "de", "num_bytes": 781577, "num_examples": 5010}, {"name": "el", "num_bytes": 1069000, "num_examples": 5010}, {"name": "es", "num_bytes": 852488, "num_examples": 5010}, {"name": "fr", "num_bytes": 860951, "num_examples": 5010}, {"name": "hi", "num_bytes": 849698, "num_examples": 5010}, {"name": "ru", "num_bytes": 898706, "num_examples": 5010}, {"name": "sw", "num_bytes": 842743, "num_examples": 5010}, {"name": "th", "num_bytes": 1098847, "num_examples": 5010}, {"name": "tr", "num_bytes": 788523, "num_examples": 5010}, {"name": "ur", "num_bytes": 786383, "num_examples": 5010}, {"name": "vi", "num_bytes": 827304, "num_examples": 5010}, {"name": "zh", "num_bytes": 1083312, "num_examples": 5010}], "download_size": 11533534, "dataset_size": 12374864}, {"config_name": "xglm-1.7B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 788487, "num_examples": 5010}, {"name": "bg", "num_bytes": 863627, "num_examples": 5010}, {"name": "de", "num_bytes": 824591, "num_examples": 5010}, {"name": "el", "num_bytes": 870729, "num_examples": 5010}, {"name": "es", "num_bytes": 856025, "num_examples": 5010}, {"name": "fr", "num_bytes": 877381, "num_examples": 5010}, {"name": "hi", "num_bytes": 973947, "num_examples": 5010}, {"name": "ru", "num_bytes": 840252, "num_examples": 5010}, {"name": "sw", "num_bytes": 784472, "num_examples": 5010}, {"name": "th", "num_bytes": 821323, "num_examples": 5010}, {"name": "tr", "num_bytes": 747863, "num_examples": 5010}, {"name": "ur", "num_bytes": 855280, "num_examples": 5010}, {"name": "vi", "num_bytes": 807745, "num_examples": 5010}, {"name": "zh", "num_bytes": 801384, "num_examples": 5010}], "download_size": 10871776, "dataset_size": 11713106}, {"config_name": "xglm-2.9B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 791983, "num_examples": 5010}, {"name": "bg", "num_bytes": 856898, "num_examples": 5010}, {"name": "de", "num_bytes": 833316, "num_examples": 5010}, {"name": "el", "num_bytes": 859152, "num_examples": 5010}, {"name": "es", "num_bytes": 875232, "num_examples": 5010}, {"name": "fr", "num_bytes": 880335, "num_examples": 5010}, {"name": "hi", "num_bytes": 754460, "num_examples": 5010}, {"name": "ru", "num_bytes": 839486, "num_examples": 5010}, {"name": "sw", "num_bytes": 807832, "num_examples": 5010}, {"name": "th", "num_bytes": 792237, "num_examples": 5010}, {"name": "tr", "num_bytes": 744151, "num_examples": 5010}, {"name": "ur", "num_bytes": 763715, "num_examples": 5010}, {"name": "vi", "num_bytes": 825575, "num_examples": 5010}, {"name": "zh", "num_bytes": 803580, "num_examples": 5010}], "download_size": 10586622, "dataset_size": 11427952}, {"config_name": "xglm-4.5B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 825461, "num_examples": 5010}, {"name": "bg", "num_bytes": 861124, "num_examples": 5010}, {"name": "de", "num_bytes": 847007, "num_examples": 5010}, {"name": "el", "num_bytes": 875762, "num_examples": 5010}, {"name": "es", "num_bytes": 871840, "num_examples": 5010}, {"name": "fr", "num_bytes": 882720, "num_examples": 5010}, {"name": "hi", "num_bytes": 826770, "num_examples": 5010}, {"name": "ru", "num_bytes": 865706, "num_examples": 5010}, {"name": "sw", "num_bytes": 807688, "num_examples": 5010}, {"name": "th", "num_bytes": 827077, "num_examples": 5010}, {"name": "tr", "num_bytes": 836039, "num_examples": 5010}, {"name": "ur", "num_bytes": 799881, "num_examples": 5010}, {"name": "vi", "num_bytes": 846648, "num_examples": 5010}, {"name": "zh", "num_bytes": 836279, "num_examples": 5010}], "download_size": 10968672, "dataset_size": 11810002}, {"config_name": "xglm-7.5B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 818748, "num_examples": 5010}, {"name": "bg", "num_bytes": 853616, "num_examples": 5010}, {"name": "de", "num_bytes": 833462, "num_examples": 5010}, {"name": "el", "num_bytes": 860997, "num_examples": 5010}, {"name": "es", "num_bytes": 855814, "num_examples": 5010}, {"name": "fr", "num_bytes": 859597, "num_examples": 5010}, {"name": "hi", "num_bytes": 788540, "num_examples": 5010}, {"name": "ru", "num_bytes": 846308, "num_examples": 5010}, {"name": "sw", "num_bytes": 813638, "num_examples": 5010}, {"name": "th", "num_bytes": 793438, "num_examples": 5010}, {"name": "tr", "num_bytes": 753138, "num_examples": 5010}, {"name": "ur", "num_bytes": 811513, "num_examples": 5010}, {"name": "vi", "num_bytes": 829040, "num_examples": 5010}, {"name": "zh", "num_bytes": 823480, "num_examples": 5010}], "download_size": 10699999, "dataset_size": 11541329}, {"config_name": "bloom-560m", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 793192, "num_examples": 5010}, {"name": "bg", "num_bytes": 1293032, "num_examples": 5026}, {"name": "de", "num_bytes": 853267, "num_examples": 5011}, {"name": "el", "num_bytes": 853650, "num_examples": 5028}, {"name": "es", "num_bytes": 790401, "num_examples": 5019}, {"name": "fr", "num_bytes": 785706, "num_examples": 5022}, {"name": "hi", "num_bytes": 815413, "num_examples": 5020}, {"name": "ru", "num_bytes": 1119100, "num_examples": 5035}, {"name": "sw", "num_bytes": 1283629, "num_examples": 5010}, {"name": "th", "num_bytes": 1927388, "num_examples": 5010}, {"name": "tr", "num_bytes": 1136397, "num_examples": 5010}, {"name": "ur", "num_bytes": 806534, "num_examples": 5050}, {"name": "vi", "num_bytes": 810195, "num_examples": 5033}, {"name": "zh", "num_bytes": 895087, "num_examples": 5013}], "download_size": 13312268, "dataset_size": 14162991}, {"config_name": "bloom-1b1", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 772035, "num_examples": 5010}, {"name": "bg", "num_bytes": 838287, "num_examples": 5010}, {"name": "de", "num_bytes": 816688, "num_examples": 5010}, {"name": "el", "num_bytes": 757902, "num_examples": 5010}, {"name": "es", "num_bytes": 811192, "num_examples": 5010}, {"name": "fr", "num_bytes": 823552, "num_examples": 5010}, {"name": "hi", "num_bytes": 755051, "num_examples": 5010}, {"name": "ru", "num_bytes": 802154, "num_examples": 5010}, {"name": "sw", "num_bytes": 769220, "num_examples": 5010}, {"name": "th", "num_bytes": 855265, "num_examples": 5010}, {"name": "tr", "num_bytes": 1009235, "num_examples": 5010}, {"name": "ur", "num_bytes": 784984, "num_examples": 5010}, {"name": "vi", "num_bytes": 798443, "num_examples": 5010}, {"name": "zh", "num_bytes": 795561, "num_examples": 5010}], "download_size": 10548239, "dataset_size": 11389569}, {"config_name": "bloom-1b7", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 817013, "num_examples": 5010}, {"name": "bg", "num_bytes": 803575, "num_examples": 5010}, {"name": "de", "num_bytes": 811977, "num_examples": 5010}, {"name": "el", "num_bytes": 768757, "num_examples": 5010}, {"name": "es", "num_bytes": 834218, "num_examples": 5010}, {"name": "fr", "num_bytes": 844544, "num_examples": 5010}, {"name": "hi", "num_bytes": 780516, "num_examples": 5010}, {"name": "ru", "num_bytes": 856927, "num_examples": 5010}, {"name": "sw", "num_bytes": 745814, "num_examples": 5010}, {"name": "th", "num_bytes": 930774, "num_examples": 5010}, {"name": "tr", "num_bytes": 871417, "num_examples": 5010}, {"name": "ur", "num_bytes": 751069, "num_examples": 5010}, {"name": "vi", "num_bytes": 814194, "num_examples": 5010}, {"name": "zh", "num_bytes": 790631, "num_examples": 5010}], "download_size": 10580096, "dataset_size": 11421426}, {"config_name": "bloom-3b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 819238, "num_examples": 5010}, {"name": "bg", "num_bytes": 822686, "num_examples": 5010}, {"name": "de", "num_bytes": 850318, "num_examples": 5010}, {"name": "el", "num_bytes": 809037, "num_examples": 5010}, {"name": "es", "num_bytes": 850349, "num_examples": 5010}, {"name": "fr", "num_bytes": 855581, "num_examples": 5010}, {"name": "hi", "num_bytes": 797905, "num_examples": 5010}, {"name": "ru", "num_bytes": 861096, "num_examples": 5010}, {"name": "sw", "num_bytes": 767209, "num_examples": 5010}, {"name": "th", "num_bytes": 820321, "num_examples": 5010}, {"name": "tr", "num_bytes": 881668, "num_examples": 5010}, {"name": "ur", "num_bytes": 810843, "num_examples": 5010}, {"name": "vi", "num_bytes": 828926, "num_examples": 5010}, {"name": "zh", "num_bytes": 793476, "num_examples": 5010}], "download_size": 10727323, "dataset_size": 11568653}, {"config_name": "bloom-7b1", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 834767, "num_examples": 5010}, {"name": "bg", "num_bytes": 848921, "num_examples": 5010}, {"name": "de", "num_bytes": 827646, "num_examples": 5010}, {"name": "el", "num_bytes": 886001, "num_examples": 5010}, {"name": "es", "num_bytes": 859775, "num_examples": 5010}, {"name": "fr", "num_bytes": 863548, "num_examples": 5010}, {"name": "hi", "num_bytes": 814484, "num_examples": 5010}, {"name": "ru", "num_bytes": 860392, "num_examples": 5010}, {"name": "sw", "num_bytes": 811380, "num_examples": 5010}, {"name": "th", "num_bytes": 775738, "num_examples": 5010}, {"name": "tr", "num_bytes": 747961, "num_examples": 5010}, {"name": "ur", "num_bytes": 836727, "num_examples": 5010}, {"name": "vi", "num_bytes": 836042, "num_examples": 5010}, {"name": "zh", "num_bytes": 814866, "num_examples": 5010}], "download_size": 10776918, "dataset_size": 11618248}, {"config_name": "llama-7B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 792437, "num_examples": 5010}, {"name": "bg", "num_bytes": 855365, "num_examples": 5010}, {"name": "de", "num_bytes": 844453, "num_examples": 5010}, {"name": "el", "num_bytes": 864748, "num_examples": 5010}, {"name": "es", "num_bytes": 871358, "num_examples": 5010}, {"name": "fr", "num_bytes": 882671, "num_examples": 5010}, {"name": "hi", "num_bytes": 791631, "num_examples": 5010}, {"name": "ru", "num_bytes": 853745, "num_examples": 5010}, {"name": "sw", "num_bytes": 753655, "num_examples": 5010}, {"name": "th", "num_bytes": 787365, "num_examples": 5010}, {"name": "tr", "num_bytes": 814193, "num_examples": 5010}, {"name": "ur", "num_bytes": 811987, "num_examples": 5010}, {"name": "vi", "num_bytes": 807334, "num_examples": 5010}, {"name": "zh", "num_bytes": 841441, "num_examples": 5010}], "download_size": 10731053, "dataset_size": 11572383}, {"config_name": "llama-13B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 833799, "num_examples": 5010}, {"name": "bg", "num_bytes": 850755, "num_examples": 5010}, {"name": "de", "num_bytes": 842498, "num_examples": 5010}, {"name": "el", "num_bytes": 853859, "num_examples": 5010}, {"name": "es", "num_bytes": 865884, "num_examples": 5010}, {"name": "fr", "num_bytes": 872326, "num_examples": 5010}, {"name": "hi", "num_bytes": 803350, "num_examples": 5010}, {"name": "ru", "num_bytes": 850066, "num_examples": 5010}, {"name": "sw", "num_bytes": 785595, "num_examples": 5010}, {"name": "th", "num_bytes": 794461, "num_examples": 5010}, {"name": "tr", "num_bytes": 789769, "num_examples": 5010}, {"name": "ur", "num_bytes": 813459, "num_examples": 5010}, {"name": "vi", "num_bytes": 783219, "num_examples": 5010}, {"name": "zh", "num_bytes": 828885, "num_examples": 5010}], "download_size": 10726595, "dataset_size": 11567925}, {"config_name": "RedPajama-INCITE-Base-3B-v1", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 815395, "num_examples": 5010}, {"name": "bg", "num_bytes": 870568, "num_examples": 5010}, {"name": "de", "num_bytes": 830593, "num_examples": 5010}, {"name": "el", "num_bytes": 887938, "num_examples": 5010}, {"name": "es", "num_bytes": 866523, "num_examples": 5010}, {"name": "fr", "num_bytes": 880668, "num_examples": 5010}, {"name": "hi", "num_bytes": 871126, "num_examples": 5010}, {"name": "ru", "num_bytes": 875379, "num_examples": 5010}, {"name": "sw", "num_bytes": 775459, "num_examples": 5010}, {"name": "th", "num_bytes": 829562, "num_examples": 5010}, {"name": "tr", "num_bytes": 813161, "num_examples": 5010}, {"name": "ur", "num_bytes": 812296, "num_examples": 5010}, {"name": "vi", "num_bytes": 824340, "num_examples": 5010}, {"name": "zh", "num_bytes": 892427, "num_examples": 5010}], "download_size": 11004105, "dataset_size": 11845435}, {"config_name": "RedPajama-INCITE-7B-Base", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 789074, "num_examples": 5010}, {"name": "bg", "num_bytes": 870916, "num_examples": 5010}, {"name": "de", "num_bytes": 845436, "num_examples": 5010}, {"name": "el", "num_bytes": 850780, "num_examples": 5010}, {"name": "es", "num_bytes": 875677, "num_examples": 5010}, {"name": "fr", "num_bytes": 880989, "num_examples": 5010}, {"name": "hi", "num_bytes": 751526, "num_examples": 5010}, {"name": "ru", "num_bytes": 881090, "num_examples": 5010}, {"name": "sw", "num_bytes": 746100, "num_examples": 5010}, {"name": "th", "num_bytes": 685496, "num_examples": 5010}, {"name": "tr", "num_bytes": 770359, "num_examples": 5010}, {"name": "ur", "num_bytes": 708810, "num_examples": 5010}, {"name": "vi", "num_bytes": 735197, "num_examples": 5010}, {"name": "zh", "num_bytes": 848461, "num_examples": 5010}], "download_size": 10398581, "dataset_size": 11239911}, {"config_name": "llama-30B", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 860301, "num_examples": 5010}, {"name": "bg", "num_bytes": 863946, "num_examples": 5010}, {"name": "de", "num_bytes": 858009, "num_examples": 5010}, {"name": "el", "num_bytes": 874347, "num_examples": 5010}, {"name": "es", "num_bytes": 875007, "num_examples": 5010}, {"name": "fr", "num_bytes": 884764, "num_examples": 5010}, {"name": "hi", "num_bytes": 846950, "num_examples": 5010}, {"name": "ru", "num_bytes": 869708, "num_examples": 5010}, {"name": "sw", "num_bytes": 857197, "num_examples": 5010}, {"name": "th", "num_bytes": 847402, "num_examples": 5010}, {"name": "tr", "num_bytes": 825879, "num_examples": 5010}, {"name": "ur", "num_bytes": 860074, "num_examples": 5010}, {"name": "vi", "num_bytes": 862456, "num_examples": 5010}, {"name": "zh", "num_bytes": 849263, "num_examples": 5010}], "download_size": 11193973, "dataset_size": 12035303}, {"config_name": "open_llama_3b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 705142, "num_examples": 5010}, {"name": "bg", "num_bytes": 875604, "num_examples": 5010}, {"name": "de", "num_bytes": 851525, "num_examples": 5010}, {"name": "el", "num_bytes": 739635, "num_examples": 5010}, {"name": "es", "num_bytes": 866291, "num_examples": 5010}, {"name": "fr", "num_bytes": 880556, "num_examples": 5010}, {"name": "hi", "num_bytes": 392659, "num_examples": 5010}, {"name": "ru", "num_bytes": 876933, "num_examples": 5010}, {"name": "sw", "num_bytes": 738299, "num_examples": 5010}, {"name": "th", "num_bytes": 1273724, "num_examples": 5010}, {"name": "tr", "num_bytes": 769184, "num_examples": 5010}, {"name": "ur", "num_bytes": 739162, "num_examples": 5010}, {"name": "vi", "num_bytes": 701661, "num_examples": 5010}, {"name": "zh", "num_bytes": 878129, "num_examples": 5010}], "download_size": 10447174, "dataset_size": 11288504}, {"config_name": "open_llama_7b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 765568, "num_examples": 5010}, {"name": "bg", "num_bytes": 860978, "num_examples": 5010}, {"name": "de", "num_bytes": 839878, "num_examples": 5010}, {"name": "el", "num_bytes": 790038, "num_examples": 5010}, {"name": "es", "num_bytes": 862624, "num_examples": 5010}, {"name": "fr", "num_bytes": 871243, "num_examples": 5010}, {"name": "hi", "num_bytes": 328421, "num_examples": 5010}, {"name": "ru", "num_bytes": 867424, "num_examples": 5010}, {"name": "sw", "num_bytes": 784318, "num_examples": 5010}, {"name": "th", "num_bytes": 1133537, "num_examples": 5010}, {"name": "tr", "num_bytes": 770420, "num_examples": 5010}, {"name": "ur", "num_bytes": 739842, "num_examples": 5010}, {"name": "vi", "num_bytes": 767095, "num_examples": 5010}, {"name": "zh", "num_bytes": 840369, "num_examples": 5010}], "download_size": 10380425, "dataset_size": 11221755}, {"config_name": "open_llama_13b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 855506, "num_examples": 5010}, {"name": "bg", "num_bytes": 860868, "num_examples": 5010}, {"name": "de", "num_bytes": 845896, "num_examples": 5010}, {"name": "el", "num_bytes": 789495, "num_examples": 5010}, {"name": "es", "num_bytes": 874595, "num_examples": 5010}, {"name": "fr", "num_bytes": 883531, "num_examples": 5010}, {"name": "hi", "num_bytes": 349430, "num_examples": 5010}, {"name": "ru", "num_bytes": 860441, "num_examples": 5010}, {"name": "sw", "num_bytes": 819611, "num_examples": 5010}, {"name": "th", "num_bytes": 1249012, "num_examples": 5010}, {"name": "tr", "num_bytes": 813974, "num_examples": 5010}, {"name": "ur", "num_bytes": 775914, "num_examples": 5010}, {"name": "vi", "num_bytes": 826589, "num_examples": 5010}, {"name": "zh", "num_bytes": 828483, "num_examples": 5010}], "download_size": 10792015, "dataset_size": 11633345}, {"config_name": "xgen-7b-4k-base", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 815916, "num_examples": 5010}, {"name": "bg", "num_bytes": 866698, "num_examples": 5010}, {"name": "de", "num_bytes": 845296, "num_examples": 5010}, {"name": "el", "num_bytes": 873279, "num_examples": 5010}, {"name": "es", "num_bytes": 867614, "num_examples": 5010}, {"name": "fr", "num_bytes": 878177, "num_examples": 5010}, {"name": "hi", "num_bytes": 795679, "num_examples": 5010}, {"name": "ru", "num_bytes": 870241, "num_examples": 5010}, {"name": "sw", "num_bytes": 815925, "num_examples": 5010}, {"name": "th", "num_bytes": 680865, "num_examples": 5010}, {"name": "tr", "num_bytes": 808508, "num_examples": 5010}, {"name": "ur", "num_bytes": 755658, "num_examples": 5010}, {"name": "vi", "num_bytes": 798616, "num_examples": 5010}, {"name": "zh", "num_bytes": 839810, "num_examples": 5010}], "download_size": 10670952, "dataset_size": 11512282}, {"config_name": "xgen-7b-8k-base", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 822039, "num_examples": 5010}, {"name": "bg", "num_bytes": 866105, "num_examples": 5010}, {"name": "de", "num_bytes": 834487, "num_examples": 5010}, {"name": "el", "num_bytes": 871714, "num_examples": 5010}, {"name": "es", "num_bytes": 863765, "num_examples": 5010}, {"name": "fr", "num_bytes": 874570, "num_examples": 5010}, {"name": "hi", "num_bytes": 811916, "num_examples": 5010}, {"name": "ru", "num_bytes": 863980, "num_examples": 5010}, {"name": "sw", "num_bytes": 801837, "num_examples": 5010}, {"name": "th", "num_bytes": 773394, "num_examples": 5010}, {"name": "tr", "num_bytes": 812359, "num_examples": 5010}, {"name": "ur", "num_bytes": 762615, "num_examples": 5010}, {"name": "vi", "num_bytes": 845558, "num_examples": 5010}, {"name": "zh", "num_bytes": 840984, "num_examples": 5010}], "download_size": 10803993, "dataset_size": 11645323}, {"config_name": "xgen-7b-8k-inst", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 852293, "num_examples": 5010}, {"name": "bg", "num_bytes": 877290, "num_examples": 5010}, {"name": "de", "num_bytes": 843890, "num_examples": 5010}, {"name": "el", "num_bytes": 900388, "num_examples": 5010}, {"name": "es", "num_bytes": 871938, "num_examples": 5010}, {"name": "fr", "num_bytes": 883776, "num_examples": 5010}, {"name": "hi", "num_bytes": 819611, "num_examples": 5010}, {"name": "ru", "num_bytes": 871868, "num_examples": 5010}, {"name": "sw", "num_bytes": 903297, "num_examples": 5010}, {"name": "th", "num_bytes": 781456, "num_examples": 5010}, {"name": "tr", "num_bytes": 888386, "num_examples": 5010}, {"name": "ur", "num_bytes": 835512, "num_examples": 5010}, {"name": "vi", "num_bytes": 881933, "num_examples": 5010}, {"name": "zh", "num_bytes": 886819, "num_examples": 5010}], "download_size": 11257127, "dataset_size": 12098457}, {"config_name": "open_llama_7b_v2", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 799618, "num_examples": 5010}, {"name": "bg", "num_bytes": 864517, "num_examples": 5010}, {"name": "de", "num_bytes": 844605, "num_examples": 5010}, {"name": "el", "num_bytes": 867881, "num_examples": 5010}, {"name": "es", "num_bytes": 872871, "num_examples": 5010}, {"name": "fr", "num_bytes": 883623, "num_examples": 5010}, {"name": "hi", "num_bytes": 821085, "num_examples": 5010}, {"name": "ru", "num_bytes": 875313, "num_examples": 5010}, {"name": "sw", "num_bytes": 810855, "num_examples": 5010}, {"name": "th", "num_bytes": 756931, "num_examples": 5010}, {"name": "tr", "num_bytes": 832938, "num_examples": 5010}, {"name": "ur", "num_bytes": 776355, "num_examples": 5010}, {"name": "vi", "num_bytes": 841205, "num_examples": 5010}, {"name": "zh", "num_bytes": 836994, "num_examples": 5010}], "download_size": 10843461, "dataset_size": 11684791}, {"config_name": "polylm-1.7b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 840312, "num_examples": 5010}, {"name": "bg", "num_bytes": 766907, "num_examples": 5010}, {"name": "de", "num_bytes": 846775, "num_examples": 5010}, {"name": "el", "num_bytes": 985392, "num_examples": 5010}, {"name": "es", "num_bytes": 850661, "num_examples": 5010}, {"name": "fr", "num_bytes": 872488, "num_examples": 5010}, {"name": "hi", "num_bytes": 947295, "num_examples": 5010}, {"name": "ru", "num_bytes": 823812, "num_examples": 5010}, {"name": "sw", "num_bytes": 639344, "num_examples": 5010}, {"name": "th", "num_bytes": 873714, "num_examples": 5010}, {"name": "tr", "num_bytes": 882916, "num_examples": 5010}, {"name": "ur", "num_bytes": 707398, "num_examples": 5010}, {"name": "vi", "num_bytes": 837592, "num_examples": 5010}, {"name": "zh", "num_bytes": 811983, "num_examples": 5010}], "download_size": 10845259, "dataset_size": 11686589}, {"config_name": "polylm-13b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 856622, "num_examples": 5010}, {"name": "bg", "num_bytes": 872936, "num_examples": 5010}, {"name": "de", "num_bytes": 853814, "num_examples": 5010}, {"name": "el", "num_bytes": 792171, "num_examples": 5010}, {"name": "es", "num_bytes": 867823, "num_examples": 5010}, {"name": "fr", "num_bytes": 876800, "num_examples": 5010}, {"name": "hi", "num_bytes": 825863, "num_examples": 5010}, {"name": "ru", "num_bytes": 876390, "num_examples": 5010}, {"name": "sw", "num_bytes": 659651, "num_examples": 5010}, {"name": "th", "num_bytes": 848574, "num_examples": 5010}, {"name": "tr", "num_bytes": 801914, "num_examples": 5010}, {"name": "ur", "num_bytes": 750495, "num_examples": 5010}, {"name": "vi", "num_bytes": 847699, "num_examples": 5010}, {"name": "zh", "num_bytes": 823542, "num_examples": 5010}], "download_size": 10712964, "dataset_size": 11554294}, {"config_name": "polylm-multialpaca-13b", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 832229, "num_examples": 5010}, {"name": "bg", "num_bytes": 873130, "num_examples": 5010}, {"name": "de", "num_bytes": 846302, "num_examples": 5010}, {"name": "el", "num_bytes": 846617, "num_examples": 5010}, {"name": "es", "num_bytes": 861183, "num_examples": 5010}, {"name": "fr", "num_bytes": 863929, "num_examples": 5010}, {"name": "hi", "num_bytes": 938018, "num_examples": 5010}, {"name": "ru", "num_bytes": 866081, "num_examples": 5010}, {"name": "sw", "num_bytes": 802054, "num_examples": 5010}, {"name": "th", "num_bytes": 836126, "num_examples": 5010}, {"name": "tr", "num_bytes": 799768, "num_examples": 5010}, {"name": "ur", "num_bytes": 909124, "num_examples": 5010}, {"name": "vi", "num_bytes": 842588, "num_examples": 5010}, {"name": "zh", "num_bytes": 823529, "num_examples": 5010}], "download_size": 11099348, "dataset_size": 11940678}, {"config_name": "open_llama_3b_v2", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 692849, "num_examples": 5010}, {"name": "bg", "num_bytes": 852675, "num_examples": 5010}, {"name": "de", "num_bytes": 835619, "num_examples": 5010}, {"name": "el", "num_bytes": 834201, "num_examples": 5010}, {"name": "es", "num_bytes": 873160, "num_examples": 5010}, {"name": "fr", "num_bytes": 881098, "num_examples": 5010}, {"name": "hi", "num_bytes": 726395, "num_examples": 5010}, {"name": "ru", "num_bytes": 853657, "num_examples": 5010}, {"name": "sw", "num_bytes": 690930, "num_examples": 5010}, {"name": "th", "num_bytes": 724712, "num_examples": 5010}, {"name": "tr", "num_bytes": 755625, "num_examples": 5010}, {"name": "ur", "num_bytes": 753648, "num_examples": 5010}, {"name": "vi", "num_bytes": 795981, "num_examples": 5010}, {"name": "zh", "num_bytes": 844200, "num_examples": 5010}], "download_size": 10273420, "dataset_size": 11114750}, {"config_name": "Llama-2-7b-hf", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 833964, "num_examples": 5010}, {"name": "bg", "num_bytes": 867408, "num_examples": 5010}, {"name": "de", "num_bytes": 852305, "num_examples": 5010}, {"name": "el", "num_bytes": 859363, "num_examples": 5010}, {"name": "es", "num_bytes": 880162, "num_examples": 5010}, {"name": "fr", "num_bytes": 886400, "num_examples": 5010}, {"name": "hi", "num_bytes": 802665, "num_examples": 5010}, {"name": "ru", "num_bytes": 868568, "num_examples": 5010}, {"name": "sw", "num_bytes": 775118, "num_examples": 5010}, {"name": "th", "num_bytes": 774722, "num_examples": 5010}, {"name": "tr", "num_bytes": 810268, "num_examples": 5010}, {"name": "ur", "num_bytes": 786428, "num_examples": 5010}, {"name": "vi", "num_bytes": 841904, "num_examples": 5010}, {"name": "zh", "num_bytes": 837126, "num_examples": 5010}], "download_size": 10835071, "dataset_size": 11676401}, {"config_name": "Llama-2-13b-hf", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 838926, "num_examples": 5010}, {"name": "bg", "num_bytes": 864619, "num_examples": 5010}, {"name": "de", "num_bytes": 847106, "num_examples": 5010}, {"name": "el", "num_bytes": 858400, "num_examples": 5010}, {"name": "es", "num_bytes": 873274, "num_examples": 5010}, {"name": "fr", "num_bytes": 878414, "num_examples": 5010}, {"name": "hi", "num_bytes": 819446, "num_examples": 5010}, {"name": "ru", "num_bytes": 864307, "num_examples": 5010}, {"name": "sw", "num_bytes": 821998, "num_examples": 5010}, {"name": "th", "num_bytes": 812673, "num_examples": 5010}, {"name": "tr", "num_bytes": 812102, "num_examples": 5010}, {"name": "ur", "num_bytes": 831111, "num_examples": 5010}, {"name": "vi", "num_bytes": 838971, "num_examples": 5010}, {"name": "zh", "num_bytes": 835539, "num_examples": 5010}], "download_size": 10955556, "dataset_size": 11796886}, {"config_name": "Llama-2-7b-chat-hf", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 948578, "num_examples": 5010}, {"name": "bg", "num_bytes": 776309, "num_examples": 5010}, {"name": "de", "num_bytes": 725534, "num_examples": 5010}, {"name": "el", "num_bytes": 956805, "num_examples": 5010}, {"name": "es", "num_bytes": 631915, "num_examples": 5010}, {"name": "fr", "num_bytes": 534372, "num_examples": 5010}, {"name": "hi", "num_bytes": 960220, "num_examples": 5010}, {"name": "ru", "num_bytes": 535448, "num_examples": 5010}, {"name": "sw", "num_bytes": 1001740, "num_examples": 5010}, {"name": "th", "num_bytes": 995206, "num_examples": 5010}, {"name": "tr", "num_bytes": 865992, "num_examples": 5010}, {"name": "ur", "num_bytes": 864017, "num_examples": 5010}, {"name": "vi", "num_bytes": 246890, "num_examples": 5010}, {"name": "zh", "num_bytes": 538232, "num_examples": 5010}], "download_size": 9739928, "dataset_size": 10581258}, {"config_name": "Llama-2-13b-chat-hf", "features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "neutral", "2": "contradiction"}}}}], "splits": [{"name": "ar", "num_bytes": 932439, "num_examples": 5010}, {"name": "bg", "num_bytes": 877857, "num_examples": 5010}, {"name": "de", "num_bytes": 859893, "num_examples": 5010}, {"name": "el", "num_bytes": 910487, "num_examples": 5010}, {"name": "es", "num_bytes": 872553, "num_examples": 5010}, {"name": "fr", "num_bytes": 879291, "num_examples": 5010}, {"name": "hi", "num_bytes": 987002, "num_examples": 5010}, {"name": "ru", "num_bytes": 887918, "num_examples": 5010}, {"name": "sw", "num_bytes": 1021074, "num_examples": 5010}, {"name": "th", "num_bytes": 1054387, "num_examples": 5010}, {"name": "tr", "num_bytes": 900761, "num_examples": 5010}, {"name": "ur", "num_bytes": 1099374, "num_examples": 5010}, {"name": "vi", "num_bytes": 884472, "num_examples": 5010}, {"name": "zh", "num_bytes": 882394, "num_examples": 5010}], "download_size": 12208572, "dataset_size": 13049902}]}
TAGS
#language-English #region-us 

Dataset Card for "xnli"
=======================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository:
* Paper:
* Point of Contact:
* Size of downloaded dataset files: 7.74 GB
* Size of the generated dataset: 3.23 GB
* Total amount of disk used: 10.97 GB


### Dataset Summary


XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels).


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### all\_languages


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 1.61 GB
* Total amount of disk used: 2.09 GB


An example of 'train' looks as follows.


#### ar


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 109.32 MB
* Total amount of disk used: 593.29 MB


An example of 'validation' looks as follows.


#### bg


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 128.32 MB
* Total amount of disk used: 612.28 MB


An example of 'train' looks as follows.


#### de


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 86.17 MB
* Total amount of disk used: 570.14 MB


An example of 'train' looks as follows.


#### el


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 142.30 MB
* Total amount of disk used: 626.26 MB


An example of 'validation' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### all\_languages


* 'premise': a multilingual 'string' variable, with possible languages including 'ar', 'bg', 'de', 'el', 'en'.
* 'hypothesis': a multilingual 'string' variable, with possible languages including 'ar', 'bg', 'de', 'el', 'en'.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2).


#### ar


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2).


#### bg


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2).


#### de


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2).


#### el


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2).


### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions


Thanks to @lewtun, @mariamabarham, @thomwolf, @lhoestq, @patrickvonplaten for adding this dataset.



### Dataset Summary


XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels). ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### all\_languages


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 1.61 GB
* Total amount of disk used: 2.09 GB


An example of 'train' looks as follows. #### ar


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 109.32 MB
* Total amount of disk used: 593.29 MB


An example of 'validation' looks as follows. #### bg


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 128.32 MB
* Total amount of disk used: 612.28 MB


An example of 'train' looks as follows. #### de


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 86.17 MB
* Total amount of disk used: 570.14 MB


An example of 'train' looks as follows. #### el


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 142.30 MB
* Total amount of disk used: 626.26 MB


An example of 'validation' looks as follows. ### Data Fields


The data fields are the same among all splits. #### all\_languages


* 'premise': a multilingual 'string' variable, with possible languages including 'ar', 'bg', 'de', 'el', 'en'.
* 'hypothesis': a multilingual 'string' variable, with possible languages including 'ar', 'bg', 'de', 'el', 'en'.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### ar


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### bg


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### de


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### el


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @lewtun, @mariamabarham, @thomwolf, @lhoestq, @patrickvonplaten for adding this dataset.
TAGS
#language-English #region-us 
 ### Dataset Summary


XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels). ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### all\_languages


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 1.61 GB
* Total amount of disk used: 2.09 GB


An example of 'train' looks as follows. #### ar


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 109.32 MB
* Total amount of disk used: 593.29 MB


An example of 'validation' looks as follows. #### bg


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 128.32 MB
* Total amount of disk used: 612.28 MB


An example of 'train' looks as follows. #### de


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 86.17 MB
* Total amount of disk used: 570.14 MB


An example of 'train' looks as follows. #### el


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 142.30 MB
* Total amount of disk used: 626.26 MB


An example of 'validation' looks as follows. ### Data Fields


The data fields are the same among all splits. #### all\_languages


* 'premise': a multilingual 'string' variable, with possible languages including 'ar', 'bg', 'de', 'el', 'en'.
* 'hypothesis': a multilingual 'string' variable, with possible languages including 'ar', 'bg', 'de', 'el', 'en'.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### ar


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### bg


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### de


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). #### el


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'neutral' (1), 'contradiction' (2). ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @lewtun, @mariamabarham, @thomwolf, @lhoestq, @patrickvonplaten for adding this dataset.
passage: TAGS
#language-English #region-us 
### Dataset Summary


XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels).### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------### Data Instances#### all\_languages


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 1.61 GB
* Total amount of disk used: 2.09 GB


An example of 'train' looks as follows.#### ar


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 109.32 MB
* Total amount of disk used: 593.29 MB


An example of 'validation' looks as follows.#### bg


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 128.32 MB
* Total amount of disk used: 612.28 MB


An example of 'train' looks as follows.#### de


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 86.17 MB
* Total amount of disk used: 570.14 MB


An example of 'train' looks as follows.#### el


* Size of downloaded dataset files: 483.96 MB
* Size of the generated dataset: 142.30 MB
* Total amount of disk used: 626.26 MB


An example of 'validation' looks as follows.### Data Fields


The data fields are the same among all splits.