wmt19

참고자료:

cs-ko

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/cs-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 7270695
'validation' 2983년
  • 특징 : 
{
    "translation": {
        "languages": [
            "cs",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

디엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/de-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 38690334
'validation' 2998년
  • 특징 : 
{
    "translation": {
        "languages": [
            "de",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

fi-en

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/fi-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 6587448
'validation' 3000
  • 특징 : 
{
    "translation": {
        "languages": [
            "fi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

구엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/gu-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 11670
'validation' 1998년
  • 특징 : 
{
    "translation": {
        "languages": [
            "gu",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

ㅋㅋ엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/kk-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 126583
'validation' 2066년
  • 특징 : 
{
    "translation": {
        "languages": [
            "kk",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

lt-en

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/lt-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 2344893
'validation' 2000
  • 특징 : 
{
    "translation": {
        "languages": [
            "lt",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

루엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/ru-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 37492126
'validation' 3000
  • 특징 : 
{
    "translation": {
        "languages": [
            "ru",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

zh-en

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/zh-en')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 25984574
'validation' 3981
  • 특징 : 
{
    "translation": {
        "languages": [
            "zh",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

fr-de

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt19/fr-de')
  • 설명 :
Translate dataset based on the data from statmt.org.

Versions exists for the different years using a combination of multiple data
sources. The base `wmt_translate` allows you to create your own config to choose
your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.


config = datasets.wmt.WmtConfig(
    version="0.0.1",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
builder = datasets.builder("wmt_translate", config=config)
  • 라이센스 : 알려진 라이센스 없음
  • 버전 : 1.0.0
  • 분할 :
나뉘다 예
'train' 9824476
'validation' 1512
  • 특징 :
{
    "translation": {
        "languages": [
            "fr",
            "de"
        ],
        "id": null,
        "_type": "Translation"
    }
}