References:
ar
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/ar')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
bg
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/bg')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
de
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/de')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
el
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/el')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
en
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/en')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
es
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/es')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
fr
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/fr')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
hi
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/hi')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
ru
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/ru')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
sw
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/sw')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
th
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/th')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
tr
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/tr')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
ur
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/ur')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
vi
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/vi')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
zh
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/zh')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
all_languages
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:xnli/all_languages')
- Description:
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).
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
5010 |
'train' |
392702 |
'validation' |
2490 |
- Features:
{
"premise": {
"languages": [
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh"
],
"id": null,
"_type": "Translation"
},
"hypothesis": {
"languages": [
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh"
],
"num_languages": 15,
"id": null,
"_type": "TranslationVariableLanguages"
},
"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}