wmt16

참고자료:

cs-ko

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt16/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' 2999
'train' 997240
'validation' 2656
  • 특징 : 
{
    "translation": {
        "languages": [
            "cs",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

디엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt16/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' 2999
'train' 4548885
'validation' 2169
  • 특징 : 
{
    "translation": {
        "languages": [
            "de",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

fi-en

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:wmt16/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' 6000
'train' 2073394
'validation' 1370
  • 특징 : 
{
    "translation": {
        "languages": [
            "fi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

로엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요. 

ds = tfds.load('huggingface:wmt16/ro-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' 1999년
'train' 610320
'validation' 1999년
  • 특징 : 
{
    "translation": {
        "languages": [
            "ro",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

루엔

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요. 

ds = tfds.load('huggingface:wmt16/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' 2998년
'train' 1516162
'validation' 2818
  • 특징 : 
{
    "translation": {
        "languages": [
            "ru",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}

트렌

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요. 

ds = tfds.load('huggingface:wmt16/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' 1001
  • 특징 : 
{
    "translation": {
        "languages": [
            "tr",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    }
}