rm error-badline

app.py

@@ -25,10 +25,10 @@ BATCH_SIZE = 32
 PRE_TRAINED_MODEL_NAME = "distilbert-base-uncased"
 
 #import all data
-data=pd.read_csv('./data/train.csv',engine='python',encoding='utf-8', error_bad_lines=False)
-test=pd.read_csv('./data/test.csv',engine='python',encoding='utf-8', error_bad_lines=False)
-test_labels=pd.read_csv('./data/test_labels.csv',engine='python',encoding='utf-8', error_bad_lines=False)
-sub=pd.read_csv('./data/sample_submission.csv',engine='python',encoding='utf-8', error_bad_lines=False)
+data=pd.read_csv('./data/train.csv',engine='python',encoding='utf-8')
+test=pd.read_csv('./data/test.csv',engine='python',encoding='utf-8')
+test_labels=pd.read_csv('./data/test_labels.csv',engine='python',encoding='utf-8')
+sub=pd.read_csv('./data/sample_submission.csv',engine='python',encoding='utf-8')
 
 #setup data
 data.drop(columns='id',inplace=True)
@@ -217,6 +217,6 @@ model = model.to(device)
 #sub.insert(1,"tweet",data.comment_text,True)
 #sub.to_csv("sub.csv", encoding='utf-8', index=False)
 #^commented above code, saved to csv to reduce wait/comput time
-sub=pd.read_csv('./data/sub.csv',engine='python',encoding='utf-8', error_bad_lines=False)
+sub=pd.read_csv('./data/sub.csv',engine='python',encoding='utf-8')
 sub.drop(index="id")
 st.dataframe(sub)