head_qa

Références:

es

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:head_qa/es')
  • Descriptif :
HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the
Spanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio
de Sanidad, Consumo y Bienestar Social.

The dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology.
  • Licence : Licence MIT
  • Version : 1.1.0
  • Fractionnements :
Diviser Exemples
'test' 2742
'train' 2657
'validation' 1366
  • Caractéristiques :
{
    "name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "year": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "qid": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "qtext": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ra": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "image": {
        "id": null,
        "_type": "Image"
    },
    "answers": [
        {
            "aid": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "atext": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        }
    ]
}

fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:head_qa/en')
  • Descriptif :
HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the
Spanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio
de Sanidad, Consumo y Bienestar Social.

The dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology.
  • Licence : Licence MIT
  • Version : 1.1.0
  • Fractionnements :
Diviser Exemples
'test' 2742
'train' 2657
'validation' 1366
  • Caractéristiques :
{
    "name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "year": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "qid": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "qtext": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ra": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "image": {
        "id": null,
        "_type": "Image"
    },
    "answers": [
        {
            "aid": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "atext": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        }
    ]
}