सन्दर्भ:
किताबें
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:subjqa/books')
- विवरण :
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.1.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 345 |
'train' | 1314 |
'validation' | 256 |
- विशेषताएँ :
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
इलेक्ट्रानिक्स
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:subjqa/electronics')
- विवरण :
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.1.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 358 |
'train' | 1295 |
'validation' | 255 |
- विशेषताएँ :
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
किराना
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:subjqa/grocery')
- विवरण :
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.1.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 591 |
'train' | 1124 |
'validation' | 218 |
- विशेषताएँ :
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
फिल्में
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:subjqa/movies')
- विवरण :
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.1.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 291 |
'train' | 1369 |
'validation' | 261 |
- विशेषताएँ :
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रेस्टोरेंट
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:subjqa/restaurants')
- विवरण :
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.1.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 266 |
'train' | 1400 |
'validation' | 267 |
- विशेषताएँ :
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ट्रिपएडवाइज़र
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:subjqa/tripadvisor')
- विवरण :
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.1.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 512 |
'train' | 1165 |
'validation' | 230 |
- विशेषताएँ :
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}