Update app.py

app.py

@@ -2,12 +2,15 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 import gradio as gr
 import torch
 
-title = "IEEE CIS Summer School - 2023"
+
+title = "IEEE Summer School"
 description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
 examples = [["How are you?"]]
 
-tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill", padding_side='left')  # Set padding_side='left'
-model = AutoModelForCausalLM.from_pretrained("facebook/blenderbot-400M-distill")
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
+
 
 def predict(input, history=[]):
     # tokenize the new input sentence
@@ -24,7 +27,7 @@ def predict(input, history=[]):
     ).tolist()
 
     # convert the tokens to text, and then split the responses into lines
-    response = tokenizer.decode(history[0]).split("")
+    response = tokenizer.decode(history[0]).split("<|endoftext|>")
     # print('decoded_response-->>'+str(response))
     response = [
         (response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)
@@ -32,6 +35,7 @@ def predict(input, history=[]):
     # print('response-->>'+str(response))
     return response, history
 
+
 gr.Interface(
     fn=predict,
     title=title,