Loi tokenzier

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer, GenerationConfig
+from transformers import pipeline, AutoModelForSeq2SeqLM, BartTokenizer, GenerationConfig
 from diffusers import StableDiffusionPipeline
 import torch
 import io
@@ -7,12 +7,12 @@ from PIL import Image
 
 # Load the summarization model (lacos03/bart-base-finetuned-xsum) manually
 model_name = "lacos03/bart-base-finetuned-xsum"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+tokenizer = BartTokenizer.from_pretrained(model_name, use_fast=False)  # Use slow tokenizer
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
 # Create a custom GenerationConfig to fix early_stopping issue
 generation_config = GenerationConfig.from_pretrained(model_name)
-generation_config.early_stopping = True  # Set to True to fix the error
+generation_config.early_stopping = True  # Fix early_stopping error
 
 # Initialize the summarization pipeline
 summarizer = pipeline(