Update app.py

app.py

@@ -11,6 +11,7 @@ from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.feature_extraction.text import TfidfVectorizer
 
 model = pickle.load(open('spam_model.sav','rb'))
+tf = pickle.load(open('vectorizer.pkl','rb'))
 
 st.title('Spam classifier')
 input = st.text_area('Enter sms here')
@@ -21,7 +22,7 @@ review = review.split()
 review = [ps.stem(word) for word in review if not word in stopwords.words('english')]
 review = ' '.join(review)
 
-tf = TfidfVectorizer()
+
 X = tf.fit_transform(review).toarray()