Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st 
 import torch
 from torch import nn
-from transformers import BertModel, AutoTokenizer, AutoModel, pipeline
+from transformers import BertModel, AutoTokenizer 
 from time import time
 import matplotlib.pyplot as plt
 # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -58,11 +58,11 @@ def inference(txt):
 
 def infer_and_display_result(txt):
     start_time = time()
-
+    st.subheader("Inference results:")    
+    
     res = inference(txt)
     res.sort(key = lambda x : - x[1])
     
-    st.subheader("Inference results:")    
     for lbl, score in res:
         if score >=1:
             st.write(f"[        {lbl:<7}] {labels_decoder[lbl]:<35}  {score:.1f}%")
@@ -98,7 +98,7 @@ comment = """This application estimates probability that certain article belongs
 - 'stat.ML': 'Machine Learning (stat)',
 - 'cs.CV': 'Computer Vision',
 - 'cs.LG': 'Machine Learning' """.replace("'", '')
-st.code(comment)
+st.markdown(comment)
 
 text1 = st.text_area("ENTER ARTICLE TITLE OR ABSTRACT HERE:")
 text2 = '' # st.text_area("ENTER ARTICLE ABSTRACT HERE")