Update app.py

app.py

@@ -26,14 +26,7 @@ st.markdown(style, unsafe_allow_html=True)
 st.markdown('<p style="font-family:sans-serif;font-size: 1.9rem;"> HertogAI Table Q&A using TAPAS and Model Language</p>', unsafe_allow_html=True)
 st.markdown('<p style="font-family:sans-serif;font-size: 1.0rem;"> This code is based on Jordan Skinner. I enhanced his work for Data analysis COUNT, AVG, TOTAL, MEAN & StdDev </p>', unsafe_allow_html=True)
 st.markdown("<p style='font-family:sans-serif;font-size: 1.2rem;'>Pre-trained TAPAS model runs on max 64 rows and 32 columns data. Make sure the file data doesn't exceed these dimensions.</p>", unsafe_allow_html=True)
-st.markdown("""
-    <style>
-        .custom-font {
-            font-family: sans-serif;
-            font-size: 2.5rem;
-        }
-    </style>
-""", unsafe_allow_html=True)
+
 
 # Initialize TAPAS pipeline
 tqa = pipeline(task="table-question-answering", 
@@ -47,7 +40,14 @@ t5_model = T5ForConditionalGeneration.from_pretrained("t5-small")
 # File uploader in the sidebar
 file_name = st.sidebar.file_uploader("Upload file:", type=['csv', 'xlsx'])
 
-
+st.markdown("""
+    <style>
+        .custom-font {
+            font-family: sans-serif;
+            font-size: 2.5rem;
+        }
+    </style>
+""", unsafe_allow_html=True)
 
 # File processing and question answering
 if file_name is None: