Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import numpy as np
 from Ai import chatbot, chatbot2, chatbot3, chatbot4, chatbot5, chatbot7, chatbot11
 from huggingface_hub import InferenceClient
-def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temperature,top_p, top_k):
+def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temperature,top_p):
     m=torch.load("./model.pt")
     
     messages = [{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}]
@@ -21,7 +21,7 @@ def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temper
     prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
     p=pipe.tokenizer.apply_chat_template([{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}], tokenize=False, add_generation_prompt=True)
     o= pipe(p, max_new_tokens=max_tokens, do_sample=True, temperature=0.1)
-    outputs = pipe(prompt, max_new_tokens=max_tokens, do_sample=True, temperature=temperature, top_k=top_k, top_p=top_p)
+    outputs = pipe(prompt, max_new_tokens=max_tokens, do_sample=True, temperature=temperature, top_p=top_p)
     return outputs[0]["generated_text"]
 import random
 from diffusers import DiffusionPipeline
@@ -538,8 +538,7 @@ a8= gr.ChatInterface(
             value=0.1,
             step=0.05,
             label="Top-p (nucleus sampling)",
-        ),
-        gr.Slider(minimum=0.1, maximum=1.0, step=0.05,label="Top-k")
+        )
     ],
 )