Update app.py

app.py

@@ -153,8 +153,8 @@ with gr.Blocks(css=custom_css) as interface:
                 value=["yolov5"],
                 label="Select Model(s)",
             )
-            with gr.Row(elem_classes="custom-row"):
-                run_button = gr.Button("Run", elem_classes="custom-button")
+            #with gr.Row(elem_classes="custom-row"):
+            run_button = gr.Button("Run", elem_classes="custom-button")
 
 
         with gr.Column():
@@ -182,11 +182,11 @@ with gr.Blocks(css=custom_css) as interface:
     )
     
     gr.Markdown("""
-        Concept Discovery involves identifying interpretable high-level features or concepts within a deep learning model's representation. It aims to understand what a model has learned and how these learned features relate to meaningful attributes in the data.
+        ##Concept Discovery involves identifying interpretable high-level features or concepts within a deep learning model's representation. It aims to understand what a model has learned and how these learned features relate to meaningful attributes in the data.
 
-        Deep Feature Factorization (DFF) is a technique that decomposes the deep features learned by a model into disentangled and interpretable components. It typically involves matrix factorization methods applied to activation maps, enabling the identification of semantically meaningful concepts captured by the model.
+        ##Deep Feature Factorization (DFF) is a technique that decomposes the deep features learned by a model into disentangled and interpretable components. It typically involves matrix factorization methods applied to activation maps, enabling the identification of semantically meaningful concepts captured by the model.
 
-        Together, these methods enhance model interpretability and provide insights into the decision-making process of neural networks.
+        ##Together, these methods enhance model interpretability and provide insights into the decision-making process of neural networks.
 
     """)
     with gr.Row(elem_classes="custom-row"):