Ссылки:
ru
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/en')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
да
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/da')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
де
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/de')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
Нидерланды
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/nl')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
св
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/sv')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 42490 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
бг
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/bg')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 15986 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
CS
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/cs')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 23187 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
час
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/hr')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 7944 |
'validation' | 2500 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
пожалуйста
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/pl')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 23197 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ск
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/sk')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 22971 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
сл
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/sl')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 23184 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
эс
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/es')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 52785 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
пт
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/fr')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
это
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/it')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
пт
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/pt')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 52370 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ро
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/ro')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 15921 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
и др.
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/et')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 23126 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
фи
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/fi')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 42497 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ху
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/hu')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 22664 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
лт
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/lt')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 23188 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
лв
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/lv')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 23208 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
эль
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/el')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
тонна
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/mt')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 17521 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
все_языки
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:multi_eurlex/all_languages')
- Описание :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- Лицензия : Нет известной лицензии.
- Версия : 1.0.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- Функции :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"languages": [
"en",
"da",
"de",
"nl",
"sv",
"bg",
"cs",
"hr",
"pl",
"sk",
"sl",
"es",
"fr",
"it",
"pt",
"ro",
"et",
"fi",
"hu",
"lt",
"lv",
"el",
"mt"
],
"id": null,
"_type": "Translation"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}