참고자료:
예
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:head_qa/es')
- 설명 :
HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the
Spanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio
de Sanidad, Consumo y Bienestar Social.
The dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology.
- 라이센스 : MIT 라이센스
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2742 |
'train' | 2657 |
'validation' | 1366 |
- 특징 :
{
"name": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"qid": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"qtext": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"ra": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"image": {
"id": null,
"_type": "Image"
},
"answers": [
{
"aid": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"atext": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
]
}
ko
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:head_qa/en')
- 설명 :
HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the
Spanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio
de Sanidad, Consumo y Bienestar Social.
The dataset contains questions about the following topics: medicine, nursing, psychology, chemistry, pharmacology and biology.
- 라이센스 : MIT 라이센스
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2742 |
'train' | 2657 |
'validation' | 1366 |
- 특징 :
{
"name": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"qid": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"qtext": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"ra": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"image": {
"id": null,
"_type": "Image"
},
"answers": [
{
"aid": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"atext": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
]
}