tokenizer from my own moel

app.py

@@ -12,7 +12,7 @@ from torch.utils.data import TensorDataset, random_split
 from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 from transformers import BertForSequenceClassification, AdamW, BertConfig
 import random
-tokenizer = AutoTokenizer.from_pretrained('bert-base-multilingual-cased')
+tokenizer = AutoTokenizer.from_pretrained('armansakif/bengali-fake-news')
 
 model = BertForSequenceClassification.from_pretrained(
     "armansakif/bengali-fake-news", # Use the 12-layer BERT model, with an uncased vocab.