Update app.py

app.py

@@ -62,18 +62,21 @@ def read_pdf(file):
 #     # Display the extracted text
 #     #st.text(extracted_text)
 #     return extracted_text
-    
-@st.cache(suppress_st_warning=True)
-def engsum(text):
+@st.cache
+def l():
     tokenizer = AutoTokenizer.from_pretrained('t5-base')
     model = AutoModelWithLMHead.from_pretrained('t5-base', return_dict=True)
+    return tokenizer, model
+@st.cache(suppress_st_warning=True)
+def engsum(text):
+    tokenizer, model = l()
 	#st.text("Using Google T5 Transformer ..")
     inputs = tokenizer.encode("summarize: " + text,return_tensors='pt',
 										max_length= 512,
 										truncation=True)
     summary_ids = model.generate(inputs, max_length=150, min_length=80, length_penalty=5., num_beams=2)
     summary = tokenizer.decode(summary_ids[0])
-    st.success(summary)
+    st.success(summary[5:-2])
 @st.cache(suppress_st_warning=True)
 def bansum(text):
     def query(payload):