Update app.py

app.py

@@ -220,12 +220,12 @@ with gr.Blocks() as demo:
                 num_tokens = gr.Number(value="5", label="num tokens to represent each object", interactive= True)
                 num_tokens_global = num_tokens
                 embedding_learning_rate = gr.Textbox(value="0.00025", label="Embedding optimization: Learning rate", interactive= True )
-                max_emb_train_steps =  gr.Number(value="6", maximum=100, label="embedding optimization: Training steps", interactive= True )
+                max_emb_train_steps =  gr.Number(value="6", maximum="100", label="embedding optimization: Training steps", interactive= True )
                 
                 diffusion_model_learning_rate = gr.Textbox(value="0.0002", label="UNet Optimization: Learning rate", interactive= True )
-                max_diffusion_train_steps = gr.Number(value="28", label="UNet Optimization: Learning rate: Training steps", interactive= True )
+                max_diffusion_train_steps = gr.Number(value="28", maximum="200", label="UNet Optimization: Learning rate: Training steps", interactive= True )
                 
-                train_batch_size = gr.Number(value="20", maximum=200, label="Batch size", interactive= True )
+                train_batch_size = gr.Number(value="20", label="Batch size", interactive= True )
                 gradient_accumulation_steps=gr.Number(value="2", label="Gradient accumulation", interactive= True )
             
             def run_optimization_wrapper (