млсум

Ссылки:

де

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:mlsum/de')
  • Описание :
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. 
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish. 
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community. 
We report cross-lingual comparative analyses based on state-of-the-art systems. 
These highlight existing biases which motivate the use of a multi-lingual dataset.
  • Лицензия : Нет известной лицензии.
  • Версия : 1.0.0
  • Расколы :
Расколоть Примеры
'test' 10701
'train' 220887
'validation' 11394
  • Функции : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "summary": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

эс

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:mlsum/es')
  • Описание :
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. 
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish. 
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community. 
We report cross-lingual comparative analyses based on state-of-the-art systems. 
These highlight existing biases which motivate the use of a multi-lingual dataset.
  • Лицензия : Нет известной лицензии.
  • Версия : 1.0.0
  • Расколы :
Расколоть Примеры
'test' 13920
'train' 266367
'validation' 10358
  • Функции : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "summary": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

пт

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:mlsum/fr')
  • Описание :
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. 
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish. 
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community. 
We report cross-lingual comparative analyses based on state-of-the-art systems. 
These highlight existing biases which motivate the use of a multi-lingual dataset.
  • Лицензия : Нет известной лицензии.
  • Версия : 1.0.0
  • Расколы :
Расколоть Примеры
'test' 15828
'train' 392902
'validation' 16059
  • Функции : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "summary": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ру

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:mlsum/ru')
  • Описание :
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. 
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish. 
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community. 
We report cross-lingual comparative analyses based on state-of-the-art systems. 
These highlight existing biases which motivate the use of a multi-lingual dataset.
  • Лицензия : Нет известной лицензии.
  • Версия : 1.0.0
  • Расколы :
Расколоть Примеры
'test' 757
'train' 25556
'validation' 750
  • Функции : 
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "summary": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ты

Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:

ds = tfds.load('huggingface:mlsum/tu')
  • Описание :
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. 
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish. 
Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community. 
We report cross-lingual comparative analyses based on state-of-the-art systems. 
These highlight existing biases which motivate the use of a multi-lingual dataset.
  • Лицензия : Нет известной лицензии.
  • Версия : 1.0.0
  • Расколы :
Расколоть Примеры
'test' 12775
'train' 249277
'validation' 11565
  • Функции :
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "summary": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}