Conv_ai

مراجع:

• شفرة
• معانقة

conv_ai

استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:

ds = tfds.load('huggingface:conv_ai/conv_ai')

• وصف :

ConvAI is a dataset of human-to-bot conversations labelled for quality. This data can be used to train a metric for evaluating dialogue systems. Moreover, it can be used in the development of chatbots themselves: it contains the information on the quality of utterances and entire dialogues, that can guide a dialogue system in search of better answers.

• الترخيص : لا يوجد ترخيص معروف
• الإصدار : 1.0.0
• الإنشقاقات :

ينقسم	أمثلة
'train'	2778

• سمات :

{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "dialogId": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "context": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "users": [
        {
            "userType": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "id": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        }
    ],
    "evaluation": [
        {
            "breadth": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "userId": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "quality": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "engagement": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        }
    ],
    "thread": [
        {
            "evaluation": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "userId": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "time": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        }
    ]
}