medmcqa

참조:

• 암호
• 허깅페이스

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:medmcqa')

• 설명 :

MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. 
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.
The dataset contains questions about the following topics: Anesthesia, Anatomy, Biochemistry, Dental, ENT, Forensic Medicine (FM)
Obstetrics and Gynecology (O&G), Medicine, Microbiology, Ophthalmology, Orthopedics Pathology, Pediatrics, Pharmacology, Physiology, 
Psychiatry, Radiology Skin, Preventive & Social Medicine (PSM) and Surgery

• 라이선스 : 아파치 라이선스 2.0
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opa": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opb": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opc": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opd": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "cop": {
        "num_classes": 4,
        "names": [
            "a",
            "b",
            "c",
            "d"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "choice_type": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "exp": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "subject_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

참조:

• 암호
• 허깅페이스

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:medmcqa')

• 설명 :

MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. 
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.
The dataset contains questions about the following topics: Anesthesia, Anatomy, Biochemistry, Dental, ENT, Forensic Medicine (FM)
Obstetrics and Gynecology (O&G), Medicine, Microbiology, Ophthalmology, Orthopedics Pathology, Pediatrics, Pharmacology, Physiology, 
Psychiatry, Radiology Skin, Preventive & Social Medicine (PSM) and Surgery

• 라이선스 : 아파치 라이선스 2.0
• 버전 : 1.1.0
• 분할 :

• 특징 :

{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opa": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opb": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opc": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "opd": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "cop": {
        "num_classes": 4,
        "names": [
            "a",
            "b",
            "c",
            "d"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "choice_type": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "exp": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "subject_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}