Update app.py

app.py

@@ -9,9 +9,9 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
 @st.cache
 def load_models():
     tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
-    bert_mlm_positive = BertForMaskedLM.from_pretrained('text_style_mlm_positive', return_dict=True).to(device).train(True)
-    bert_mlm_negative = BertForMaskedLM.from_pretrained('text_style_mlm_negative', return_dict=True).to(device).train(True)
-    bert_classifier = BertForSequenceClassification.from_pretrained('text_style_classifier', num_labels=2).to(device).train(True)
+    bert_mlm_positive = BertForMaskedLM.from_pretrained('any0019/text_style_mlm_positive', return_dict=True).to(device).train(True)
+    bert_mlm_negative = BertForMaskedLM.from_pretrained('any0019/text_style_mlm_negative', return_dict=True).to(device).train(True)
+    bert_classifier = BertForSequenceClassification.from_pretrained('any0019/text_style_classifier', num_labels=2).to(device).train(True)
     return tokenizer, bert_mlm_positive, bert_mlm_negative, bert_classifier