Referencias:
vuelos
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/flights')
- Descripción :
Taskmaster is dataset for goal oriented conversations. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 2481 |
- Características :
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"_type": "Value"
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"instruction_id": {
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}
]
}
pedidos de comida
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/food-ordering')
- Descripción :
Taskmaster is dataset for goal oriented conversationas. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 1050 |
- Características :
{
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"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
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"utterances": [
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{
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]
}
]
}
]
}
hoteles
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/hotels')
- Descripción :
Taskmaster is dataset for goal oriented conversationas. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 2357 |
- Características :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
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]
}
]
}
películas
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/movies')
- Descripción :
Taskmaster is dataset for goal oriented conversationas. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 3056 |
- Características :
{
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"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
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]
}
]
}
]
}
música
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/music')
- Descripción :
Taskmaster is dataset for goal oriented conversationas. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 1603 |
- Características :
{
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"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
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]
}
]
}
búsqueda de restaurante
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/restaurant-search')
- Descripción :
Taskmaster is dataset for goal oriented conversationas. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 3276 |
- Características :
{
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"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
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}
]
}
Deportes
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:taskmaster2/sports')
- Descripción :
Taskmaster is dataset for goal oriented conversationas. The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. In this way, users were led to believe they were interacting with an automated system that “spoke” using text-to-speech (TTS) even though it was in fact a human behind the scenes. As a result, users could express themselves however they chose in the context of an automated interface.
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'train' | 3481 |
- Características :
{
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"instruction_id": {
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}