सब्जका

सन्दर्भ:

• कोड
• गले लगाना

पुस्तकें

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"
    }
}

चलचित्र

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"
    }
}