Update summary.py

summary.py

@@ -1,12 +1,16 @@
 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)
+
 def summarize(passage):
     txt = " ".join(passage)
-    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)
     batch = tokenizer(txt, truncation=True, padding='longest', return_tensors="pt").to(device)
     translated = model.generate(**batch)
     summy = tokenizer.batch_decode(translated, skip_special_tokens=True)