Update app.py

app.py

@@ -42,10 +42,10 @@ with site_header:
    
 
 with tweet_input:
-    st.header('Is Your Tweet Considered Hate Speech?')
+    st.header('Is Your Text Considered Toxic?')
     st.write("""*Please note that this prediction is based on how the model was trained, so it may not be an accurate representation.*""")
     # user input here
-    user_text = st.text_input('Enter Tweet', max_chars=280) # setting input as user_text
+    user_text = st.text_input('Enter Text', max_chars=280) # setting input as user_text
 
 with model_results:    
     st.subheader('Prediction:')
@@ -72,13 +72,13 @@ with model_results:
         X_test_count = tfidf.transform(X_test)
 
         # loading in model
-        final_model = joblib.load(open('resources/final_bayes.pickle', 'rb'))
+        final_model = joblib.load(open('final_bayes.pickle', 'rb'))
 
         # apply model to make predictions
         prediction = final_model.predict(X_test_count[0])
 
         if prediction == 0:
-            st.subheader('**Not Hate Speech**')
+            st.subheader('**Not Toxic**')
         else:
-            st.subheader('**Hate Speech**')
+            st.subheader('**Toxic**')
         st.text('')