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from datasets import load_dataset
import pandas as pd
divider = 1
data_size = 25000 // divider
case_size = data_size // 2
dataset = load_dataset("imdb")
train_df = pd.DataFrame(dataset['train'])
test_df = pd.DataFrame(dataset['test'])
train_df = train_df.iloc[::divider, :]
test_df = test_df.iloc[::divider, :]
train_df['label'] = train_df['label'].apply(lambda x: 'NEGATIVE' if x == 0 else 'POSITIVE')
test_df['label'] = test_df['label'].apply(lambda x: 'NEGATIVE' if x == 0 else 'POSITIVE')
train_df.to_csv(f'imdb_train_{case_size}_{case_size}.csv', index=False)
test_df.to_csv(f'imdb_test_{case_size}_{case_size}.csv', index=False)
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