karena_e

Referensi:

v1.0

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:cos_e/v1.0')

Keterangan :

Common Sense Explanations (CoS-E) allows for training language models to
automatically generate explanations that can be used during training and
inference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.

Lisensi : Tidak ada lisensi yang diketahui
Versi : 1.0.0
Perpecahan :

Membelah	Contoh
`'train'`	7610
`'validation'`	950

Fitur :

{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choices": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "abstractive_explanation": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "extractive_explanation": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

v1.11

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:cos_e/v1.11')

Keterangan :

Common Sense Explanations (CoS-E) allows for training language models to
automatically generate explanations that can be used during training and
inference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.

Lisensi : Tidak ada lisensi yang diketahui
Versi : 1.11.0
Perpecahan :

Membelah	Contoh
`'train'`	9741
`'validation'`	1221

Fitur :

{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choices": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "abstractive_explanation": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "extractive_explanation": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}