Download Dataset/triviaqa/dataset/construct.py from KashiwaByte/DISC-Assignment: direct link, hf CLI and curl.
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https://huggingface.co/datasets/KashiwaByte/DISC-Assignment/resolve/main/Dataset/triviaqa/dataset/construct.py
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hf download hf://datasets/KashiwaByte/DISC-Assignment/Dataset/triviaqa/dataset/construct.py
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curl -L -o construct.py https://huggingface.co/datasets/KashiwaByte/DISC-Assignment/resolve/main/Dataset/triviaqa/dataset/construct.py
1.2 kB
| import re | |
| import csv | |
| import json | |
| import pandas as pd | |
| # df = pd.read_parquet('train-00000-of-00001-288b64d2a0003a2f.parquet') | |
| # 将数据框保存为CSV文件,并设置escapechar参数 | |
| # df.to_csv('train_triviaqa.csv',encoding="utf-8",escapechar='\\') | |
| csv_file = 'train_triviaqa.csv' | |
| jsonl_file = 'TriviaQA_train.jsonl' | |
| # 生成JSONL文件 | |
| messages = [] | |
| with open(csv_file, 'r', encoding='utf-8') as file: | |
| reader = csv.reader((line.replace('\0', '') for line in file)) | |
| next(reader) # 跳过标题行 | |
| for row in reader: | |
| if len(row) >= 4: | |
| context = row[1] | |
| question = row[2] | |
| answers = row[3] | |
| answer = answers | |
| message={ "instruction":"As a reading comprehension expert, you will receive context and question. Please understand the given Context first and then output the answer of the question based on the Context","input": str({'context':{context},'question':{question},}),"output":f'{answer}'} | |
| messages.append(message) | |
| # 保存为JSONL文件 | |
| with open(jsonl_file, 'w', encoding='utf-8') as file: | |
| for message in messages: | |
| file.write(json.dumps(message, ensure_ascii=False) + '\n') | |