Update app.py

app.py

@@ -3,10 +3,10 @@ from sklearn.feature_extraction.text import TfidfVectorizer
 import numpy as np
 import streamlit as st
 
-vectorizer = TfidfVectorizer(use_idf=True, lowercase=True, strip_accents='ascii', stop_words='english')
-user_input = st.text_input("Enter some text:", "Default Text")
+vectorizer = load('tfidf_vectorizer.joblib')
+user_input = st.text_input("Enter some text:", "")
 if user_input is not None:
-    x = vectorizer.fit_transform(np.array(user_input))
+    x = vectorizer.transform(np.array(user_input))
     model = load('Naive_Bayes_Spam_Detection.joblib')
     pred = model.predict(x)
     st.write(pred)