Update app.py

app.py

@@ -11,14 +11,38 @@ ind_to_target = {ind: target for target, ind in target_to_ind.items()}
 
 
 st.title('papers_classifier 🤓')
-st.text("Hey! I'm papers_classifier and I'm here to help you with answering the question 'WTF is this paper about?\n'
-According to arXiv there are 8 different fields of study - Computer Science, Economics, Electrical Engineering and Systems Science, Mathematics, Physics, Quantitative Biology, \
-Quantitative Finance and Statistics. So, everything I'll tell you will be about these eight gentlemen.\n
-You need to give me paper's title and (if you have one) it's abstract. Also you need to choose classification mode - there are 2 of them:
-best prediction and top 95% which means that you'll see as many classes as I need to show you to be confident with probability at least 0.95 that the correct one is among them.\n
-After that you need to press the Get prediction button and I'll tell you to which fields of study this paper is related. \n
-")
 
+@st.cache_data
+def display_intro():
+    intro_text = """
+    Hey! I'm papers_classifier and I'm here to help you with answering the question 'WTF is this paper about?'
+    
+    According to arXiv there are 8 different fields of study:
+    - Computer Science
+    - Economics
+    - Electrical Engineering and Systems Science
+    - Mathematics
+    - Physics
+    - Quantitative Biology
+    - Quantitative Finance
+    - Statistics
+    
+    Everything I'll tell you will be about these eight fields.
+    
+    How to use me:
+    1. Give me paper's title and (if you have one) it's abstract
+    2. Choose one of two classification modes:
+       - Best prediction: Shows the most likely to be true field
+       - Top 95%: Shows multiple fields until I'm at least 95% confident that the correct one is among them
+    3. Press the 'Get prediction' button
+    4. Wait for me to tell you which fields of study this paper relates to
+    """
+    st.markdown(intro_text)
+
+# Call the function to display the introduction
+display_intro()
+
+        
 @st.cache_resource
 def load_model_and_tokenizer():
     model_name = 'distilbert/distilbert-base-cased'