Update app.py

app.py

@@ -67,13 +67,13 @@ with model_results:
 
         # instantiating count vectorizor
         tfidf = TfidfVectorizer(stop_words=stop_words)
-        X_train = joblib.load(open('main/X_train.pickel', 'rb'))
+        X_train = joblib.load(open('resources/X_train.pickel', 'rb'))
         X_test = lemmatized_output
         X_train_count = tfidf.fit_transform(X_train)
         X_test_count = tfidf.transform(X_test)
 
         # loading in model
-        final_model = joblib.load(open('final_bayes.pickle', 'rb'))
+        final_model = joblib.load(open('resources/final_bayes.pickle', 'rb'))
 
         # apply model to make predictions
         prediction = final_model.predict(X_test_count[0])