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hda_nli_hindi

References:

HDA hindi nli

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:hda_nli_hindi/HDA hindi nli')
  • Description:
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.
  • License: MIT License
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 9970
'train' 31892
'validation' 9460
  • Features:
{
    "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

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:hda_nli_hindi/hda nli hindi')
  • Description:
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.
  • License: MIT License
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 9970
'train' 31892
'validation' 9460
  • Features:
{
    "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"
    }
}