1st commit

app.py

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+import streamlit as st
+import pickel
+
+#lets load the saved vectorizer and native model
+tfidf = pickel.load(open('vectorizer.pkl','rb'))
+model = pickel.load(open('model.pkl','rb'))
+
+#saving streamlit code
+st.title("Email spam Classifier")
+input_sms = st.text_area("Enter message")
+
+if st.button('predict'):
+    #preprocess
+    transformed_sms = transform_text(input_sms)
+    #vectorize
+    vector_input = tfidf.transform([transformed_sms])
+    #predict
+    result = model.predict(vector_input)[0]
+    #display
+    if result ==1:
+        st.header("Spam")
+    else:
+        st.header("Not Spam")    

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d353a616171e314953eabebc9a78df13bb413ce897405b9a2f75bf66628f6b88
+size 96613

vectorizer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9d3d66f70e58fa10dea2bea3fc692e190473de6c8471bc8d1973b0f9f70046f7
+size 181749