Update app.py

app.py

@@ -724,9 +724,9 @@ with gr.Blocks(css="""
             labels = label_gen('LoS/NLoS Classification', deepmimo_data, scenario_name) # Generates labels for each user, classifying them as Line-of-Sight (LoS) or Non-Line-of-Sight (NLoS), and prepares the "labels" array for inclusion in the custom dataset H5 file.
             ```
         """)
-    with gr.Tab("LWM Model and Framework"):    
-        gr.Image("images/lwm_model_v2.png")
-        gr.Markdown("This figure depicts the offline pre-training and online embedding generation process for LWM. The channel is divided into fixed-size patches, which are linearly embedded and combined with positional encodings before being passed through a Transformer encoder. During self-supervised pre-training, some embeddings are masked, and LWM leverages self-attention to extract deep features, allowing the decoder to reconstruct the masked values. For downstream tasks, the generated LWM embeddings enhance performance.")
+    #with gr.Tab("LWM Model and Framework"):    
+    #    gr.Image("images/lwm_model_v2.png")
+    #    gr.Markdown("This figure depicts the offline pre-training and online embedding generation process for LWM. The channel is divided into fixed-size patches, which are linearly embedded and combined with positional encodings before being passed through a Transformer encoder. During self-supervised pre-training, some embeddings are masked, and LWM leverages self-attention to extract deep features, allowing the decoder to reconstruct the masked values. For downstream tasks, the generated LWM embeddings enhance performance.")
 
 # Launch the app
 if __name__ == "__main__":