Update app.py

app.py

@@ -7,20 +7,20 @@ def display_csv(file_path, columns_to_display):
     # Select only the specified columns
     df_selected_columns = df[columns_to_display]
     # Display the selected columns as a table
-    st.write(df_selected_columns, height=500, width=1000, unsafe_allow_html=True)
+    st.table(df_selected_columns.sort_values(by=columns_to_display[0]), height=500, width=1000)
 
 def main():
     # Hardcoded file path
     file_path = "merged-averaged-model_timings_2.1.0_12.1_NVIDIA_A10G_False.csv"
     # Columns to display
     columns_to_display = [
-        "model_name", "pretrained", "avg_score", "image_time", "text_time", 
-         "image_shape", "text_shape", 
-        "output shape", 
+        "model_name", "pretrained", "image_time", "text_time", 
+        "avg_score", "image_shape", "text_shape", "model_memory", 
+        "output shape", "torch_version", "cuda_version", "device_name", 
         "params (M)", "FLOPs (B)"
     ]  # Specify the columns you want to display
     
-    # Add a text caption
+    # 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 presented. A10G, CUDA 12.1, Torch 2.1.0")