wmt18

참고자료:

• 암호
• 포옹하는 얼굴

cs-ko

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/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
'test'	2983년
'train'	11046024
'validation'	3005

• 특징 :

{
    "translation": {
        "languages": [
            "cs",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

디엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/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
'test'	2998년
'train'	42271874
'validation'	3004

• 특징 :

{
    "translation": {
        "languages": [
            "de",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

등등

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/et-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
'test'	2000
'train'	2175873
'validation'	2000

• 특징 :

{
    "translation": {
        "languages": [
            "et",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

fi-en

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/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
'test'	3000
'train'	3280600
'validation'	6004

• 특징 :

{
    "translation": {
        "languages": [
            "fi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

ㅋㅋ엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/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
'test'	0
'train'	0
'validation'	0

• 특징 :

{
    "translation": {
        "languages": [
            "kk",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

루엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/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
'test'	3000
'train'	36858512
'validation'	3001

• 특징 :

{
    "translation": {
        "languages": [
            "ru",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

트엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/tr-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
'test'	3000
'train'	205756
'validation'	3007

• 특징 :

{
    "translation": {
        "languages": [
            "tr",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

zh-en

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt18/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
'test'	3981
'train'	25160346
'validation'	2001년

• 특징 :

{
    "translation": {
        "languages": [
            "zh",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}