Update app.py

app.py

@@ -16,7 +16,7 @@ def print_probs(logits):
   while sum <= 95:
     prob, idx = ans[i]
     text = categories[idx] + ": "+ str(np.round(prob,1)) + "%"
-    st.markdown(text)
+    st.write(text)
     sum+=prob
     i+=1
 
@@ -24,7 +24,7 @@ def make_prediction(text):
   tokenized_text = tokenizer(text, return_tensors='pt')
   with torch.no_grad():
     pred_logits = model(**tokenized_text).logits
-  st.markdown("Category probability:")
+  st.write("Category probability:")
   print_probs(pred_logits[0])
 
 
@@ -41,8 +41,20 @@ model.load_state_dict(
     )
 )
 
-st.markdown("## Hello, people!")
+# MAIN
+
+st.markdown("# Arxiv.org category classifier")
+st.markdown(" ")
 st.markdown("<img src='https://centroderecursosmarista.org/wp-content/uploads/2013/05/arvix.jpg'>", unsafe_allow_html=True)
-text = st.text_area("Введите описание статьи")
+st.markdown(" ")
+
+st.markdown("### Article Title")
+text = st.text_area("Введите название статьи", height=400)
+
+st.markdown("### Article Abstract")
+text = st.text_area("Введите описание статьи", height=400)
+
+
+
 make_prediction(text)