пара_пат

Использованная литература:

эль-эн

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

ds = tfds.load('huggingface:para_pat/el-en')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 10855
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "el",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

cs-en

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

ds = tfds.load('huggingface:para_pat/cs-en')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 78977
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "cs",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

Энь-ху

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

ds = tfds.load('huggingface:para_pat/en-hu')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 42629
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "en",
            "hu"
        ],
        "id": null,
        "_type": "Translation"
    }
}

ан-ро

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

ds = tfds.load('huggingface:para_pat/en-ro')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 48789
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "en",
            "ro"
        ],
        "id": null,
        "_type": "Translation"
    }
}

эн-ск

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

ds = tfds.load('huggingface:para_pat/en-sk')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 23410
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "en",
            "sk"
        ],
        "id": null,
        "_type": "Translation"
    }
}

англ-британский

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

ds = tfds.load('huggingface:para_pat/en-uk')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 89226
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "en",
            "uk"
        ],
        "id": null,
        "_type": "Translation"
    }
}

вс-фр

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

ds = tfds.load('huggingface:para_pat/es-fr')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 32553
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "es",
            "fr"
        ],
        "id": null,
        "_type": "Translation"
    }
}

фр-ру

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

ds = tfds.load('huggingface:para_pat/fr-ru')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 10889
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "fr",
            "ru"
        ],
        "id": null,
        "_type": "Translation"
    }
}

де-фр

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

ds = tfds.load('huggingface:para_pat/de-fr')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 1167988
  • Функции :
{
    "translation": {
        "languages": [
            "de",
            "fr"
        ],
        "id": null,
        "_type": "Translation"
    }
}

эн-джа

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

ds = tfds.load('huggingface:para_pat/en-ja')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 6170339
  • Функции :
{
    "translation": {
        "languages": [
            "en",
            "ja"
        ],
        "id": null,
        "_type": "Translation"
    }
}

ru-es

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

ds = tfds.load('huggingface:para_pat/en-es')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 649396
  • Функции :
{
    "translation": {
        "languages": [
            "en",
            "es"
        ],
        "id": null,
        "_type": "Translation"
    }
}

ан-фр

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

ds = tfds.load('huggingface:para_pat/en-fr')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 12223525
  • Функции :
{
    "translation": {
        "languages": [
            "en",
            "fr"
        ],
        "id": null,
        "_type": "Translation"
    }
}

де-эн

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

ds = tfds.load('huggingface:para_pat/de-en')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 2165054
  • Функции :
{
    "translation": {
        "languages": [
            "de",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

эн-ко

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

ds = tfds.load('huggingface:para_pat/en-ko')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 2324357
  • Функции :
{
    "translation": {
        "languages": [
            "en",
            "ko"
        ],
        "id": null,
        "_type": "Translation"
    }
}

фр-я

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

ds = tfds.load('huggingface:para_pat/fr-ja')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 313422
  • Функции :
{
    "translation": {
        "languages": [
            "fr",
            "ja"
        ],
        "id": null,
        "_type": "Translation"
    }
}

эн-ж

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

ds = tfds.load('huggingface:para_pat/en-zh')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 4897841
  • Функции :
{
    "translation": {
        "languages": [
            "en",
            "zh"
        ],
        "id": null,
        "_type": "Translation"
    }
}

en-ru

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

ds = tfds.load('huggingface:para_pat/en-ru')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 4296399
  • Функции :
{
    "translation": {
        "languages": [
            "en",
            "ru"
        ],
        "id": null,
        "_type": "Translation"
    }
}

фр-ко

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

ds = tfds.load('huggingface:para_pat/fr-ko')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 120607
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "fr",
            "ko"
        ],
        "id": null,
        "_type": "Translation"
    }
}

ру-ук

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

ds = tfds.load('huggingface:para_pat/ru-uk')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 85963
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "ru",
            "uk"
        ],
        "id": null,
        "_type": "Translation"
    }
}

эн-пт

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

ds = tfds.load('huggingface:para_pat/en-pt')
  • Описание :
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts

This dataset contains the developed parallel corpus from the open access Google
Patents dataset in 74 language pairs, comprising more than 68 million sentences
and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm
for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned.

We demonstrate the capabilities of our corpus by training Neural Machine Translation
(NMT) models for the main 9 language pairs, with a total of 18 models.
  • Лицензия : CC BY 4.0.
  • Версия : 1.1.0
  • Расколы :
Расколоть Примеры
'train' 23121
  • Функции :
{
    "index": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "family_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "translation": {
        "languages": [
            "en",
            "pt"
        ],
        "id": null,
        "_type": "Translation"
    }
}