Update app.py

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-from transformers import BartTokenizer, BartForConditionalGeneration, pipeline
+from transformers import T5Tokenizer, TFAutoModelForSeq2SeqLM, pipeline
 import zipfile
 import os
 import nltk
@@ -31,8 +31,8 @@ if not os.path.exists(model_path):
     # print("Contents of model_dir:", os.listdir(model_dir))
 else:
     # Load the tokenizer and model from the extracted directory
-    tokenizer = BartTokenizer.from_pretrained(model_path)
-    model = BartForConditionalGeneration.from_pretrained(model_path)
+    tokenizer = T5Tokenizer.from_pretrained(model_path)
+    model = TFAutoModelForSeq2SeqLM.from_pretrained(model_path)
 
     # Create a summarization pipeline
     summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)