Update app.py

app.py

@@ -44,23 +44,23 @@ def generate(your_prompt, task_prefix, max_new_tokens, repetition_penalty, tempe
     return better_prompt
 
 
-your_prompt = gr.Textbox(label="Your Prompt", info="Your Prompt that you wanna make better", interactive=True)
+your_prompt = gr.Textbox(label="Your Prompt", info="Your Prompt that you wanna make better")
 
-task_prefix = gr.Textbox(label="Task Prefix", info="The prompt prefix for how the AI should make yours better",value="Expand the following prompt to add more detail", interactive=True)
+task_prefix = gr.Textbox(label="Task Prefix", info="The prompt prefix for how the AI should make yours better",value="Expand the following prompt to add more detail")
 
-max_new_tokens = gr.Slider(value=512, minimum=250, maximum=512, step=1, interactive=True, label="Max New Tokens", info="The maximum numbers of new tokens, controls how long is the output")
+max_new_tokens = gr.Slider(value=512, minimum=250, maximum=512, step=1, label="Max New Tokens", info="The maximum numbers of new tokens, controls how long is the output")
     
-repetition_penalty = gr.Slider(value=1.2, minimum=0, maximum=2, step=0.05, interactive=True, label="Repetition Penalty", info="Penalize repeated tokens, making the AI repeat less itself")
+repetition_penalty = gr.Slider(value=1.2, minimum=0, maximum=2, step=0.05, label="Repetition Penalty", info="Penalize repeated tokens, making the AI repeat less itself")
     
-temperature = gr.Slider(value=0.5, minimum=0, maximum=1, step=0.05, interactive=True, label="Temperature", info="Higher values produce more diverse outputs")
+temperature = gr.Slider(value=0.5, minimum=0, maximum=1, step=0.05, label="Temperature", info="Higher values produce more diverse outputs")
 
 model_precision_type = gr.Dropdown(["fp16", "fp32"], value="fp16", label="Model Precision Type", info="The precision type to load the model, like fp16 which is faster, or fp32 which is more precise but more resource consuming")
 
-top_p = gr.Slider(value=1, minimum=0, maximum=2, step=0.05, interactive=True, label="Top P", info="Higher values sample more low-probability tokens")
+top_p = gr.Slider(value=1, minimum=0, maximum=2, step=0.05, label="Top P", info="Higher values sample more low-probability tokens")
 
-top_k = gr.Slider(value=50, minimum=1, maximum=100, step=1, interactive=True, label="Top K", info="Higher k means more diverse outputs by considering a range of tokens")
+top_k = gr.Slider(value=50, minimum=1, maximum=100, step=1, label="Top K", info="Higher k means more diverse outputs by considering a range of tokens")
 
-seed = gr.Slider(value=42, minimum=0, maximum=2**32-1, interactive=True, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
+seed = gr.Slider(value=42, minimum=0, maximum=2**32-1, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
 
 examples = [
     ["A storefront with 'Text to Image' written on it.", 512, 1.2, 0.5, "fp16", 1, 50, 42]