README.md

metadata

language:
  - ko
dataset_info:
  features:
    - name: index
      dtype: string
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: category
      dtype: string
    - name: image
      dtype: image
  splits:
    - name: test
      num_bytes: 9699756
      num_examples: 240
  download_size: 3342516
  dataset_size: 9699756
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*

NCSOFT/K-DTCBench 를 쓰기 좋게 바꾸어놓았습니다.

아래 코드를 이용하였습니다.

from datasets import load_dataset, Dataset
from huggingface_hub import login; login(token="YOUR TOKEN")

dataset = load_dataset("NCSOFT/K-DTCBench")

def transform_format(example):
    formatted_question = f"{example['question']}\nOptions: A: {example['choice_a']}, B: {example['choice_b']}, C: {example['choice_c']}, D: {example['choice_d']}\n주어진 선택지 중 해당 옵션의 문자로 직접 답하세요."
    
    return {
        "question": formatted_question,
        "answer": example['answer'],
        "image": example['image'],
        "index": example['index'],
        "category": example['category'],
    }

new_test_dataset = dataset['test'].map(transform_format, remove_columns=[
    'choice_a', 'choice_b', 'choice_c', 'choice_d'
])

new_dataset = {}
new_dataset['test'] = new_test_dataset

from datasets import DatasetDict
new_dataset_dict = DatasetDict(new_dataset)

new_dataset_dict.push_to_hub('Ryoo72/K-DTCBench', private=False, max_shard_size="500MB")