Update app.py

app.py

@@ -33,10 +33,11 @@ query = query.lower()
 
 if query:
     bar = st.progress(0)
+    st.subheader(":blue[searching 40123 PubMed abstracts]")
     for i in range(10):
         bar.progress((i+1)*10)
         time.sleep(.1)
-    st.subheader("searching 40123 PubMed abstracts")
+    
     model = Word2Vec.load("pubmed_model_clotting")  # you can continue training with the loaded model!
     words = list(model.wv.key_to_index)
     X = model.wv[model.wv.key_to_index]