Update app.py

model checkpoint update

app.py

@@ -8,8 +8,8 @@ import torch
 def load_model():
     """Load the PEFT model and tokenizer once and cache them"""
     base_model = AutoModelForSeq2SeqLM.from_pretrained("t5-small")
-    peft_model = PeftModel.from_pretrained(base_model, "Lakshan2003/finetuned-xsum")
-    tokenizer = AutoTokenizer.from_pretrained("Lakshan2003/finetuned-xsum")
+    peft_model = PeftModel.from_pretrained(base_model, "Lakshan2003/finetuned-t5-xsum")
+    tokenizer = AutoTokenizer.from_pretrained("Lakshan2003/finetuned-t5-xsum")
     return peft_model, tokenizer