Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.feature_extraction.text import TfidfVectorizer
@@ -6,8 +5,9 @@ from sklearn.naive_bayes import MultinomialNB
 import joblib
 import gradio as gr
 import datasets
-df_true = datasets.load_dataset('csv', data_files='True.csv')
-df_fake = datasets.load_dataset('csv', data_files='Fake.csv')
+
+df_true = pd.read_csv('True.csv')
+df_fake = pd.read_csv('Fake.csv')
 df_true['label'] = 1
 df_fake['label'] = 0
 df_combined = pd.concat([df_true, df_fake])