Update app.py

app.py

@@ -9,8 +9,7 @@ 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.")
 
-with col2:
-    st.title("Model:")
+
     if st.button('Load Model', disabled=False):   
         with st.spinner('Wait for it...'):
             
@@ -65,10 +64,11 @@ with col2:
             
                 prediction = 'Spam' if np.argmax(output.logits.cpu().numpy()).flatten().item() == 1 else 'Normal'
                 pred = 'Predicted Class: '+ prediction
-    st.header(pred)
-    text = st.text_input("Enter the text you'd like to analyze for spam.")
-    if text or st.button('Analyze'):
-        predict(text)
+                with col2:
+                    st.header(pred)
+                    text = st.text_input("Enter the text you'd like to analyze for spam.")
+                    if text or st.button('Analyze'):
+                        predict(text)