Fix tokenizer issue

app.py

@@ -1,13 +1,14 @@
 import streamlit as st
 from newspaper import Article
-from transformers import pipeline, T5Tokenizer, AutoModelForSeq2SeqLM
+from transformers import pipeline
+from transformers import T5Tokenizer, T5Model, T5ForConditionalGeneration
 
 # Load model from Hugging Face
 @st.cache_resource
 def load_summarizer():
     model_name = "cahya/t5-base-indonesian-summarization-cased"
     tokenizer = T5Tokenizer.from_pretrained(model_name)
-    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+    model = T5ForConditionalGeneration.from_pretrained(model_name)
 
     return pipeline("summarization", model=model, tokenizer=tokenizer)