Update 1

app.py

@@ -9,8 +9,6 @@ from happytransformer import HappyTextToText, TTSettings
 import torch
 from torch.nn import BCEWithLogitsLoss
 from torch.utils.data import DataLoader, TensorDataset, random_split
-from happytransformer import HappyTextToText, TTSettings
-
 
 pipe = pipeline("text-classification", model="saurabhg2083/model_bert")
 happy_tt = HappyTextToText("T5", "vennify/t5-base-grammar-correction")
@@ -18,7 +16,6 @@ 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',
           'strong', 'hierarchical', 'rigid', 'silicon valley', 'stock options', 'takes risk', 'workforce', 'autonomous',