Update app.py

app.py

@@ -17,9 +17,8 @@ classifier = pipeline("sentiment-analysis", model=mod, tokenizer=TKR)
 # result = classifier(["This is a sample text made by Sean Ramirez.", "This is another sample text."]) # leftover from initial testing
 
 if user_input is not None:
-    col = st.columns(1)
     predicts = pipeline("sentiment-analysis", model=mod, tokenizer=TKR)
 
-    col.header("Probabilities")
+    st.markdown("##Probabilities")
     for p in predicts:
-        col.subheader(f"{ p['label']}: { round(p['score'] * 100, 1)}%")
+        st.write(f"{ p['label']}: { round(p['score'] * 100, 1)}%")