Update app_training.py

app_training.py

@@ -25,17 +25,20 @@ def create_training_demo(trainer: Trainer,
                         max_lines=1,
                         placeholder='A man is surfing')
                     gr.Markdown('''
-                        - Upload a video and write a prompt describing the video.
+                        - Upload a video and write a prompt that describes the video.
                         ''')
                 with gr.Box():
                     gr.Markdown('Output Model')
                     output_model_name = gr.Text(label='Name of your model',
+                                                placeholder='The surfer man'
                                                 max_lines=1)
                     delete_existing_model = gr.Checkbox(
                         label='Delete existing model of the same name',
-                        value=False,
-                        visible=False)
-                    validation_prompt = gr.Text(label='Validation Prompt')
+                        value=False)
+                    validation_prompt = gr.Text(label='Validation Prompt', placeholder='a dog is surfing')
+                    gr.Markdown('''
+                        - The validation prompt should modify your `Training Prompt` in order to validate the model 
+                        ''')
 
             with gr.Column():
                 with gr.Box():
@@ -74,7 +77,7 @@ def create_training_demo(trainer: Trainer,
                                                       value=100,
                                                       precision=0)
                     gr.Markdown('''
-                        - The base model must be a model that is compatible with [diffusers](https://github.com/huggingface/diffusers) library.
+                        - The base model must be a Stable Diffusion model compatible with [diffusers](https://github.com/huggingface/diffusers) library.
                         - Expected time to train a model for 300 steps: ~20 minutes with T4
                         - You can check the training status by pressing the "Open logs" button if you are running this on your Space.
                         ''')