Update app.py

app.py

@@ -15,7 +15,7 @@ model._is_chat_session_activated = False
 
 max_new_tokens = 2048
 
-def predict(input, instruction, history, temperature, top_p, top_k, rep_p, max_tokens):
+def predict(input, instruction, history, temperature, top_p, top_k, max_tokens):
 
     history = history or []
     formatted_input = "<s>"
@@ -28,11 +28,10 @@ def predict(input, instruction, history, temperature, top_p, top_k, rep_p, max_t
     
     result = model.generate(
         formatted_input,
-        temperature = temperature,
+        temp = temperature,
         max_new_tokens = max_tokens,
         top_p = top_p,
         top_k = top_k,
-        repetition_penalty = rep_p,
         do_sample = True,
         stream = False,
         details = False,
@@ -54,7 +53,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             history = gr.Chatbot(label = "History", elem_id = "chatbot")
-            input = gr.Textbox(label = "Input", value = "", lines = 2)
+            input = gr.Textbox(label = "Input", value = "Hi.", lines = 2)
             instruction = gr.Textbox(label = "Instruction", value = "You are an AI chatbot.", lines = 4)
             run = gr.Button("▶")
             clear = gr.Button("🗑️")
@@ -63,14 +62,13 @@ with gr.Blocks() as demo:
             temperature = gr.Slider( minimum = 0, maximum = 2, value = 1, step = 0.01, interactive = True, label = "Temperature" )
             top_p = gr.Slider( minimum = 0.01, maximum = 0.99, value = 0.95, step = 0.01, interactive = True, label = "Top P" )
             top_k = gr.Slider( minimum = 1, maximum = 2048, value = 50, step = 1, interactive = True, label = "Top K" )
-            rep_p = gr.Slider( minimum = 0.01, maximum = 2, value = 1.2, step = 0.01, interactive = True, label = "Repetition Penalty" )
             max_tokens = gr.Slider( minimum = 1, maximum = 2048, value = 32, step = 64, interactive = True, label = "Max New Tokens" )
             
     with gr.Row():
         with gr.Column():
             output = gr.Textbox(label = "Output", value = "", lines = 50)
 
-    run.click(predict, inputs = [input, instruction, history, temperature, top_p, top_k, rep_p, max_tokens], outputs = [output, input, history])
+    run.click(predict, inputs = [input, instruction, history, temperature, top_p, top_k, max_tokens], outputs = [output, input, history])
     clear.click(clear_history, [], history)
     
 demo.queue(concurrency_count = 500, api_open = True).launch(show_api = True)