wmt18

참고자료:

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"
    }
}

트렌

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"
    }
}