hda_nli_hindi

הפניות:

HDA הינדי nli

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

ds = tfds.load('huggingface:hda_nli_hindi/HDA hindi nli')
  • תיאור :
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.
  • רישיון : רישיון MIT
  • גרסה : 1.1.0
  • פיצולים :
לְפַצֵל דוגמאות
'test' 9970
'train' 31892
'validation' 9460
  • תכונות :
{
    "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 הינדי

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

ds = tfds.load('huggingface:hda_nli_hindi/hda nli hindi')
  • תיאור :
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.
  • רישיון : רישיון MIT
  • גרסה : 1.1.0
  • פיצולים :
לְפַצֵל דוגמאות
'test' 9970
'train' 31892
'validation' 9460
  • תכונות :
{
    "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"
    }
}