Update app.py

app.py

@@ -3,13 +3,14 @@ import numpy as np
 import pickle
 import streamlit.components.v1 as components
 from sklearn.feature_extraction.text import CountVectorizer
-cv = CountVectorizer()
+
 # Load the pickled model
 def load_model():
     return pickle.load(open('Sarcasm_Detection_BernoulliNB.pkl', 'rb')) #Load model from notebook
 
 # Function for model prediction
 def model_prediction(model, features):
+    cv = CountVectorizer()
     features = cv.transform([features]).toarray()
     predicted = str(model.predict(features)[0])
     return predicted