Update app.py

app.py

@@ -293,12 +293,16 @@ def update_pricing(steps, oauth_token: Union[gr.OAuthToken, None]):
             return gr.update(visible=True), cost_preview, gr.update(visible=False), gr.update(visible=True)
         else:
             pay_disclaimer = f'''## ⚠️ {user["name"]}, your account doesn't have a payment method. Set one up <a href='https://huggingface.co/settings/billing/payment' target='_blank'>here</a> and come back here to train your LoRA<br><br>'''
-            return gr.update(visible=True), pay_disclaimer+cost_preview, gr.update(visible=True), gr.update(visible=False)
+            return gr.update(visible=True),
+
+
+
+return gr.update(visible=True), pay_disclaimer+cost_preview, gr.update(visible=True), gr.update(visible=False)
     else:
         return gr.update(visible=False), "", gr.update(visible=False), gr.update(visible=True)
 
 def swap_base_model(model):
-    return gr.update(visible=True) if model == "[dev] (high quality model, non-commercial license)" else gr.update(visible=False)    
+    return gr.update(visible=False) if model == "[schnell] (4 step fast model)" else gr.update(visible=True)    
 
 config_yaml = '''
 device: cuda:0
@@ -374,9 +378,14 @@ with gr.Blocks(theme=theme, css=css) as demo:
                         placeholder="uncommon word like p3rs0n or trtcrd, or sentence like 'in the style of CNSTLL'",
                         interactive=True,
                     )
-                which_model = gr.Radio(["[schnell] (4 step fast model)", "[dev] (high quality model, non-commercial license - available when training locally)"], label="Which base model to train?", elem_id="space_model" if is_spaces else "local_model", value="[schnell] (4 step fast model)",)
+                which_model = gr.Radio(
+                    ["[dev] (high quality model, non-commercial license)", "[schnell] (4 step fast model)"], 
+                    label="Which base model to train?", 
+                    elem_id="space_model" if is_spaces else "local_model", 
+                    value="[dev] (high quality model, non-commercial license)",
+                )
                 model_warning = gr.Markdown("""> [dev] model license is non-commercial. By choosing to fine-tune [dev], you must agree with [its license](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) and make sure the LoRA you will train and the training process you would start does not violate it.
-                """, visible=False)
+                """, visible=True)
             with gr.Group(visible=True) as image_upload:
                 with gr.Row():
                     images = gr.File(
@@ -468,7 +477,6 @@ with gr.Blocks(theme=theme, css=css) as demo:
         pip3 install -r requirements.txt
         cd ..
         ```
-
         Login with Hugging Face to access FLUX.1 [dev], choose a token with `write` permissions to push your LoRAs to the HF Hub
         ```bash
         huggingface-cli login
@@ -545,4 +553,4 @@ with gr.Blocks(theme=theme, css=css) as demo:
     demo.load(fn=swap_visibilty, outputs=main_ui)
 
 if __name__ == "__main__":
-    demo.launch(share=True, show_error=True)
+    demo.launch(share=True, show_error=True)