hda_nli_hindi

Références:

HDA hindi nli

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

ds = tfds.load('huggingface:hda_nli_hindi/HDA hindi nli')
  • Descriptif :
This dataset is a recasted version of the Hindi Discourse Analysis Dataset used to train models for Natural Language Inference Tasks in Low-Resource Languages like Hindi.
  • Licence : Licence MIT
  • Version : 1.1.0
  • Fractionnements :
Diviser Exemples
'test' 9970
'train' 31892
'validation' 9460
  • Caractéristiques :
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "not-entailment",
            "entailment"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "topic": {
        "num_classes": 5,
        "names": [
            "Argumentative",
            "Descriptive",
            "Dialogic",
            "Informative",
            "Narrative"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

hda nli hindi

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

ds = tfds.load('huggingface:hda_nli_hindi/hda nli hindi')
  • Descriptif :
This dataset is a recasted version of the Hindi Discourse Analysis Dataset used to train models for Natural Language Inference Tasks in Low-Resource Languages like Hindi.
  • Licence : Licence MIT
  • Version : 1.1.0
  • Fractionnements :
Diviser Exemples
'test' 9970
'train' 31892
'validation' 9460
  • Caractéristiques :
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "not-entailment",
            "entailment"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "topic": {
        "num_classes": 5,
        "names": [
            "Argumentative",
            "Descriptive",
            "Dialogic",
            "Informative",
            "Narrative"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}