upd 2

app.py

@@ -9,12 +9,12 @@ from happytransformer import HappyTextToText, TTSettings
 import torch
 from torch.nn import BCEWithLogitsLoss
 from torch.utils.data import DataLoader, TensorDataset, random_split
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-pipe = pipeline("text-classification", model="saurabhg2083/model_bert")
+tokenizer = AutoTokenizer.from_pretrained("saurabhg2083/model_bert")
+model = AutoModelForSequenceClassification.from_pretrained("saurabhg2083/model_bert")
 happy_tt = HappyTextToText("T5", "vennify/t5-base-grammar-correction")
 args = TTSettings(num_beams=5, min_length=1)
-model = BertForSequenceClassification.from_pretrained(save_directory)
-tokenizer = BertTokenizer.from_pretrained(save_directory)
 
 gendered_pronouns = [
           'ambition', 'driven', 'lead', 'persist', 'principle', 'decision', 'superior', 'individual', 'assertive',