cos_e

Riferimenti:

• Codice
• Abbracciare la faccia

v1.0

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

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

• Descrizione :

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.

• Licenza : nessuna licenza conosciuta
• Versione : 1.0.0
• Divide :

• Caratteristiche :

{
    "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

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

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

• Descrizione :

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.

• Licenza : nessuna licenza conosciuta
• Versione : 1.11.0
• Divide :

• Caratteristiche :

{
    "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"
    }
}