참고자료:
대화
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:meta_woz/dialogues')
- 설명 :
MetaLWOz: A Dataset of Multi-Domain Dialogues for the Fast Adaptation of Conversation Models. We introduce the Meta-Learning Wizard of Oz (MetaLWOz) dialogue dataset for developing fast adaptation methods for conversation models. This data can be used to train task-oriented dialogue models, specifically to develop methods to quickly simulate user responses with a small amount of data. Such fast-adaptation models fall into the research areas of transfer learning and meta learning. The dataset consists of 37,884 crowdsourced dialogues recorded between two human users in a Wizard of Oz setup, in which one was instructed to behave like a bot, and the other a true human user. The users are assigned a task belonging to a particular domain, for example booking a reservation at a particular restaurant, and work together to complete the task. Our dataset spans 47 domains having 227 tasks total. Dialogues are a minimum of 10 turns long.
- 라이센스 : Microsoft 연구 데이터 라이센스 계약
- 버전 : 0.0.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2319 |
'train' | 37884 |
- 특징 :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"user_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"bot_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"task_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"turns": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
작업
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:meta_woz/tasks')
- 설명 :
MetaLWOz: A Dataset of Multi-Domain Dialogues for the Fast Adaptation of Conversation Models. We introduce the Meta-Learning Wizard of Oz (MetaLWOz) dialogue dataset for developing fast adaptation methods for conversation models. This data can be used to train task-oriented dialogue models, specifically to develop methods to quickly simulate user responses with a small amount of data. Such fast-adaptation models fall into the research areas of transfer learning and meta learning. The dataset consists of 37,884 crowdsourced dialogues recorded between two human users in a Wizard of Oz setup, in which one was instructed to behave like a bot, and the other a true human user. The users are assigned a task belonging to a particular domain, for example booking a reservation at a particular restaurant, and work together to complete the task. Our dataset spans 47 domains having 227 tasks total. Dialogues are a minimum of 10 turns long.
- 라이센스 : Microsoft 연구 데이터 라이센스 계약
- 버전 : 0.0.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 14 |
'train' | 227 |
- 특징 :
{
"task_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"bot_prompt": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"bot_role": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"user_prompt": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"user_role": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}