Try to produce output

app.py

@@ -143,6 +143,7 @@ def diffusion_chat(question, eot_weight, max_it, sharpness):
     final_tokens = tokenizer.convert_ids_to_tokens(current_tokens[answer_start:])
     final_tokens = [tok for tok in final_tokens if tokenizer.convert_tokens_to_ids(tok) != eot_token_id]
     final_output = tokenizer.convert_tokens_to_string(final_tokens)
+    print(final_output)
     yield f"<b>Final Output (after {i+1} iterations):</b><br>" + final_output
 
 # --- Gradio Interface ---
@@ -161,6 +162,7 @@ demo = gr.Interface(
     ],
     outputs=gr.HTML(label="Diffusion Output"),
     title="Diffusion Language Model Chat",
+    theme="default",
     description="This interface runs a diffusion-based language model to generate answers progressively."
 )