Update app.py

app.py

@@ -14,7 +14,7 @@ model = T5ForConditionalGeneration.from_pretrained("roborovski/superprompt-v1",
 
 
 def generate(
-    prompt, history, max_new_tokens=512, repetition_penalty=1.2, temperature=0.5, top_p=1, top_k=1,
+    prompt, history, max_new_tokens=512, repetition_penalty=1.2, temperature=0.5, top_p=1, top_k=1
 ):
     
     input_text = f"{prompt}, {history}"
@@ -23,13 +23,12 @@ def generate(
     better_prompt = tokenizer.decode(outputs[0])
     return better_prompt
 
-
 additional_inputs=[
-    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"),
-    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"),
-    gr.Slider(value=0.5, minimum=0, maximum=1, step=0.05, interactive=True, label="Temperature", info="Higher values produce more diverse outputs"),
-    gr.Slider(value=1, minimum=0, maximum=2, step=0.05, interactive=True, label="Top P", info="Higher values sample more low-probability tokens"),
-    gr.Slider(value=1, minimum=1, maximum=100, step=1, interactive=True, label="Top K", info="Higher k means more diverse outputs by considering a range of tokens"),
+    gr.Slider(value=512, minimum=250, maximum=512, step=1, interactive=True, label="Max New Tokens"),
+    gr.Slider(value=1.2, minimum=0, maximum=2, step=0.05, interactive=True, label="Repetition Penalty"),
+    gr.Slider(value=0.5, minimum=0, maximum=1, step=0.05, interactive=True, label="Temperature"),
+    gr.Slider(value=1, minimum=0, maximum=2, step=0.05, interactive=True, label="Top P"),
+    gr.Slider(value=1, minimum=1, maximum=100, step=1, interactive=True, label="Top K"),
 ]
 
 examples=[["Expand the following prompt to add more detail: A storefront with 'Text to Image' written on it.", None, None ]]