Update app.py

app.py

@@ -1,7 +1,12 @@
 import streamlit as st
-from transformers import T5Tokenizer, TFAutoModelForSeq2SeqLM, pipeline
+from transformers import T5Tokenizer, AutoModelForSeq2SeqLM, pipeline
 import zipfile
 import os
+import nltk
+
+# Download NLTK data
+nltk.download('punkt')
+from nltk.tokenize import sent_tokenize
 
 # Define the path to the saved model zip file
 zip_model_path = 'T5_samsum-20240723T171755Z-001.zip'
@@ -22,7 +27,7 @@ if not os.path.exists(model_path):
 else:
     # Load the tokenizer and model
     tokenizer = T5Tokenizer.from_pretrained(model_path)
-    model = TFAutoModelForSeq2SeqLM.from_pretrained(model_path)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
 
     # Create a summarization pipeline
     summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)