Update app.py

app.py

@@ -4,7 +4,7 @@ from textblob import TextBlob
 from transformers import BertForSequenceClassification, AdamW, BertConfig
 st.set_page_config(layout='wide', initial_sidebar_state='expanded')
 col1, col2= st.columns(2)
-
+flag = False
 with col1:
     st.title("Spamd: Turkish Spam Detector")
     st.markdown("Message spam detection tool for Turkish language. Due the small size of the dataset, I decided to go with transformers         technology Google BERT. Using the Turkish pre-trained model BERTurk, I imporved the accuracy of the tool by 18 percent compared to the previous model which used fastText.")
@@ -55,10 +55,12 @@ if st.button('Load Model', disabled=False):
                 prediction = 'Spam' if np.argmax(output.logits.cpu().numpy()).flatten().item() == 1 else 'Normal'
                 pred = 'Predicted Class: '+ prediction
                 return pred
-with col2:
-    text = st.text_input("Enter the text you'd like to analyze for spam.")
-    if text or st.button('Analyze'):
-        st.header(predict(text))
+        flag = True      
+if flag:              
+    with col2:
+        text = st.text_input("Enter the text you'd like to analyze for spam.")
+        if text or st.button('Analyze'):
+            st.header(predict(text))