mlsum

مراجع:

de

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:mlsum/de')

توضیحات :

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.

مجوز : مجوز شناخته شده ای وجود ندارد
نسخه : 1.0.0
تقسیم ها :

تقسیم کنید	نمونه ها
`'test'`	10701
`'train'`	220887
`'validation'`	11394

ویژگی ها :

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es

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:mlsum/es')

توضیحات :

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.

مجوز : مجوز شناخته شده ای وجود ندارد
نسخه : 1.0.0
تقسیم ها :

تقسیم کنید	نمونه ها
`'test'`	13920
`'train'`	266367
`'validation'`	10358

ویژگی ها :

{
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}

fr

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:mlsum/fr')

توضیحات :

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.

مجوز : مجوز شناخته شده ای وجود ندارد
نسخه : 1.0.0
تقسیم ها :

تقسیم کنید	نمونه ها
`'test'`	15828
`'train'`	392902
`'validation'`	16059

ویژگی ها :

{
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ru

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:mlsum/ru')

توضیحات :

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.

مجوز : مجوز شناخته شده ای وجود ندارد
نسخه : 1.0.0
تقسیم ها :

تقسیم کنید	نمونه ها
`'test'`	757
`'train'`	25556
`'validation'`	750

ویژگی ها :

{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "summary": {
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تو

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:mlsum/tu')

توضیحات :

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.

مجوز : مجوز شناخته شده ای وجود ندارد
نسخه : 1.0.0
تقسیم ها :

تقسیم کنید	نمونه ها
`'test'`	12775
`'train'`	249277
`'validation'`	11565

ویژگی ها :

{
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    },
    "summary": {
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