conv_ai

อ้างอิง:

Conv_ai

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

ds = tfds.load('huggingface:conv_ai/conv_ai')
  • คำอธิบาย :
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.
  • ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
  • เวอร์ชัน : 1.0.0
  • แยก :
แยก ตัวอย่าง
'train' 2778
  • คุณสมบัติ :
{
    "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"
            }
        }
    ]
}