Update my_model/tabs/model_arch.py

my_model/tabs/model_arch.py

@@ -25,6 +25,7 @@ def run_model_arch() -> None:
         st.markdown("#### Abstract")
         st.markdown("""
         <div style="text-align: justify;">
+        
         Navigating the frontier of the Visual Turing Test, this research delves into multimodal learning to bridge 
         the gap between visual perception and linguistic interpretation, a foundational challenge in artificial 
         intelligence. It scrutinizes the integration of visual cognition and external knowledge, emphasizing the 
@@ -60,6 +61,7 @@ def run_model_arch() -> None:
         st.markdown("#### Design")
         st.markdown("""
         <div style="text-align: justify;">
+        
         As illustrated in architecture, the model operates through a sequential pipeline, beginning with the Image to 
         Language Transformation Module. In this module, the image undergoes simultaneous processing via image captioning 
         and object detection frozen models, aiming to comprehensively capture the visual context and cues. These models,