Update app.py

app.py

@@ -5,7 +5,7 @@ def display_csv(file_path, columns_to_display):
     # Load the CSV file using pandas
     df = pd.read_csv(file_path)
     # Select only the specified columns
-    df_selected_columns = df[columns_to_display]
+    df_selected_columns = df[columns_to_display].sort_values(by=['avg_score']).reset_index(drop=True)
     # Display the selected columns as a table
     st.dataframe(df_selected_columns.sort_values(by=columns_to_display[0]), height=500, width=1000)
 
@@ -22,7 +22,7 @@ def main():
     
     # Add header and description
     st.header("CLIP benchmarks - retrieval and inference")
-    st.write("CLIP benchmarks for inference and retrieval performance. Image size, context length and output dimensions are also included. Retrieval performance comes from https://github.com/mlfoundations/open_clip/blob/main/docs/openclip_retrieval_results.csv.\n A10G, CUDA 12.1, Torch 2.1.0")
+    st.write("CLIP benchmarks for inference and retrieval performance. Image size, context length and output dimensions are also included. Retrieval performance comes from https://github.com/mlfoundations/open_clip/blob/main/docs/openclip_retrieval_results.csv.Tested with A10G, CUDA 12.1, Torch 2.1.0")
     
     # Call the display_csv function with the hardcoded file path and selected columns
     display_csv(file_path, columns_to_display)