lama

Références :

trex

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

ds = tfds.load('huggingface:lama/trex')

Description :

LAMA is a dataset used to probe and analyze the factual and commonsense knowledge contained in pretrained language models. See https://github.com/facebookresearch/LAMA.

Licence : La licence internationale Creative Commons Attribution-Pas d'Utilisation Commerciale 4.0. voir https://github.com/facebookresearch/LAMA/blob/master/LICENSE
Version : 1.1.0
Divisions :

Diviser	Exemples
`'train'`	1304391

Caractéristiques :

{
    "uuid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_uri": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_uri": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "predicate_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_surface": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_surface": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "masked_sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "template": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "template_negated": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "description": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "type": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

équipe

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

ds = tfds.load('huggingface:lama/squad')

Description :

LAMA is a dataset used to probe and analyze the factual and commonsense knowledge contained in pretrained language models. See https://github.com/facebookresearch/LAMA.

Licence : La licence internationale Creative Commons Attribution-Pas d'Utilisation Commerciale 4.0. voir https://github.com/facebookresearch/LAMA/blob/master/LICENSE
Version : 1.1.0
Divisions :

Diviser	Exemples
`'train'`	305

Caractéristiques :

{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "negated": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "masked_sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

google_re

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

ds = tfds.load('huggingface:lama/google_re')

Description :

LAMA is a dataset used to probe and analyze the factual and commonsense knowledge contained in pretrained language models. See https://github.com/facebookresearch/LAMA.

Licence : La licence internationale Creative Commons Attribution-Pas d'Utilisation Commerciale 4.0. voir https://github.com/facebookresearch/LAMA/blob/master/LICENSE
Version : 1.1.0
Divisions :

Diviser	Exemples
`'train'`	6106

Caractéristiques :

{
    "pred": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "evidences": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "judgments": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_w": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub_aliases": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_w": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_aliases": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "uuid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "masked_sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "template": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "template_negated": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

conceptnet

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

ds = tfds.load('huggingface:lama/conceptnet')

Description :

LAMA is a dataset used to probe and analyze the factual and commonsense knowledge contained in pretrained language models. See https://github.com/facebookresearch/LAMA.

Licence : La licence internationale Creative Commons Attribution-Pas d'Utilisation Commerciale 4.0. voir https://github.com/facebookresearch/LAMA/blob/master/LICENSE
Version : 1.1.0
Divisions :

Diviser	Exemples
`'train'`	29774

Caractéristiques :

{
    "uuid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sub": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "pred": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "obj_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "masked_sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "negated": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}