Update app.py

app.py

@@ -3,13 +3,18 @@ from transformers import pipeline
 from textblob import TextBlob
 from transformers import BertForSequenceClassification, AdamW, BertConfig
 
+col1, col2= st.columns(2)
+
+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.set_page_config(layout='wide', initial_sidebar_state='expanded')
+    text = st.text_input("Enter the text you'd like to analyze for spam.")
 
 
 
-st.set_page_config(layout='wide', initial_sidebar_state='expanded')
-st.title("Spamd: Turkish Spam Detector")
-#st.markdown()
-text = st.text_input("Enter the text you'd like to analyze for spam.")
 
 
 
@@ -66,7 +71,8 @@ def predict(new_sentence):
 
     prediction = 'Spam' if np.argmax(output.logits.cpu().numpy()).flatten().item() == 1 else 'Normal'
     pred = 'Predicted Class: '+ prediction
-    st.header(pred)
+    with col2:
+        st.header(pred)
     
     #st.write('Input', namestr(new_sentence, globals()),': \n', new_sentence) 
       # Remove the namestr(new_sentence, globals()) in case of an error