Update app.py

app.py

@@ -11,9 +11,9 @@ with open('labels.pickle', 'rb') as handle:
 
 # @st.cache
 def predict_topic_by_title_and_abstract(text):
-    tokenized_text = tokenizer(text, return_tensors='pt', truncation=True)
+    tokens = tokenizer(text, return_tensors='pt', truncation=True)
     with torch.no_grad():
-        logits = model(**tokenized_text).logits
+        logits = model(**tokens).logits
     probs = torch.nn.functional.softmax(logits[0], dim=0).numpy() * 100
     ans = list(zip(probs,labels.values()))
     ans.sort(reverse=True)
@@ -40,9 +40,9 @@ st.image(image)
 st.markdown("##### This app predicts the probabilities of the article belonging to the following topics: \'biology\', \'computer science\', \'economics\', \'electrics\', \'finance\', \'math\', \'physics\', \'statistics\'.")
 st.markdown("##### To get an article topic prediction, please write down it's title, abstract, or both.")
 
-title = st.text_area("Write article title:", height=30)
+title = st.text_area("Write article title:", height=30, unsafe_allow_html=True)
 
-abstract = st.text_area("Write article abstract:", height=60)
+abstract = st.text_area("Write article abstract:", height=60, unsafe_allow_html=True)
 
 input_text = title + " " + abstract