Update app.py

app.py

@@ -1,11 +1,11 @@
 import streamlit as st
 #from transformers import T5Tokenizer, T5ForConditionalGeneration, MarianMTModel, MarianTokenizer
 import sentencepiece
-from transformers import BartTokenizer, BartForConditionalGeneration, MarianMTModel, MarianTokenizer
+from transformers import  AutoTokenizer, BartForConditionalGeneration, MarianMTModel, MarianTokenizer
 
 def load_summarization_model():
     model = BartForConditionalGeneration.from_pretrained('facebook/bart-large-cnn')
-    tokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')
+    tokenizer =  AutoTokenizer.from_pretrained('facebook/bart-large-cnn')
     return model, tokenizer
 
 summarization_model, summarization_tokenizer = load_summarization_model()
@@ -30,7 +30,7 @@ translation_models, translation_tokenizers = load_translation_models()
 
 def summarize_text(article):
     inputs = summarization_tokenizer.encode("summarize: " + article, return_tensors="pt", max_length=6000, truncation=True)
-    summary_ids = summarization_model.generate(inputs, max_length=64, min_length=10, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary_ids = summarization_model.generate(inputs, max_length=256, min_length=10, length_penalty=2.0, num_beams=4, early_stopping=True)
     return summarization_tokenizer.decode(summary_ids[0], skip_special_tokens=True)
 
 def translate_text(text, source_lang, target_lang):