सन्दर्भ:
उड़ानें
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/flights')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 2481 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
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"text": {
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"annotations": [
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}
]
}
खाना ऑर्डर करना
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/food-ordering')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 1050 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
{
"index": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"speaker": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
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"text": {
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"annotations": [
{
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}
]
}
]
}
]
}
होटल
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/hotels')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 2357 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
{
"index": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"speaker": {
"dtype": "string",
"id": null,
"_type": "Value"
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"text": {
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"annotations": [
{
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}
}
]
}
]
}
]
}
फिल्में
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/movies')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 3056 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
{
"index": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"speaker": {
"dtype": "string",
"id": null,
"_type": "Value"
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"text": {
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"annotations": [
{
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}
}
]
}
]
}
]
}
संगीत
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/music')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 1603 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
{
"index": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"speaker": {
"dtype": "string",
"id": null,
"_type": "Value"
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"text": {
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{
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"_type": "Value"
}
}
]
}
]
}
]
}
रेस्तरां-खोज
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/restaurant-search')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 3276 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
{
"index": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"speaker": {
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"id": null,
"_type": "Value"
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"id": null,
"_type": "Value"
}
}
]
}
]
}
]
}
खेल
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:taskmaster2/sports')
- विवरण :
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.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'train' | 3481 |
- विशेषताएँ :
{
"conversation_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"instruction_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"utterances": [
{
"index": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"speaker": {
"dtype": "string",
"id": null,
"_type": "Value"
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]
}