Update summary.py

summary.py

@@ -2,13 +2,13 @@ import torch
 import streamlit as st
 from transformers import PegasusForConditionalGeneration, AutoTokenizer
 
-@st.cache(allow_output_mutation=True)
-
 model_name = 'google/pegasus-cnn_dailymail'
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = PegasusForConditionalGeneration.from_pretrained(model_name).to(device)
 
+@st.cache(allow_output_mutation=True)
+
 def summarize(passage):
     txt = " ".join(passage)
     batch = tokenizer(txt, truncation=True, padding='longest', return_tensors="pt").to(device)