엑스코파

참고자료:

• 암호
• 포옹하는 얼굴

등

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/et')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language et

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

ht

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/ht')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language ht

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

그것

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/it')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language it

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

ID

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/id')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language id

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

쿠

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/qu')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language qu

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

남서

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/sw')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language sw

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

zh

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/zh')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language zh

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

고마워

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/ta')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language ta

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

일

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/th')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language th

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

tr

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/tr')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language tr

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

vi

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/vi')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language vi

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-et

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-et')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language et

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-ht

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-ht')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language ht

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-그것

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-it')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language it

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역 ID

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-id')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language id

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-sw

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-sw')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language sw

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-zh

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-zh')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language zh

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-타

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-ta')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language ta

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역일

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-th')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language th

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-tr

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-tr')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language tr

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

번역-vi

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:xcopa/translation-vi')

• 설명 :

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the
creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa English translation for language vi

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}