Update app.py

app.py

@@ -29,8 +29,8 @@ def predict(input, history=[]):
     history = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist()
 
     # convert the tokens to text, and then split the responses into the right format
-    response = tokenizer.decode(history[0]).split("<|endoftext|>")
-    response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 1)]  # convert to tuples of list
+    response = tokenizer.decode(history[0],skip_special_tokens=True).split("</s>")
+    response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)]  # convert to tuples of list
     return response, history
 
 gr.Interface(