diff --git a/egs/aishell/ASR/transformer_ctc/.decode.py.swp b/egs/aishell/ASR/transformer_ctc/.decode.py.swp
index d10f07cfd..685a7f1ad 100644
Binary files a/egs/aishell/ASR/transformer_ctc/.decode.py.swp and b/egs/aishell/ASR/transformer_ctc/.decode.py.swp differ
diff --git a/egs/aishell/ASR/transformer_ctc/.train.py.swp b/egs/aishell/ASR/transformer_ctc/.train.py.swp
index 4c6579080..54528f1be 100644
Binary files a/egs/aishell/ASR/transformer_ctc/.train.py.swp and b/egs/aishell/ASR/transformer_ctc/.train.py.swp differ
diff --git a/egs/aishell/ASR/transformer_ctc/decode.py b/egs/aishell/ASR/transformer_ctc/decode.py
index 06cf5e12a..6515ce88c 100755
--- a/egs/aishell/ASR/transformer_ctc/decode.py
+++ b/egs/aishell/ASR/transformer_ctc/decode.py
@@ -505,7 +505,8 @@ def main():
 
         if not hasattr(HLG, "lm_scores"):
             HLG.lm_scores = HLG.scores.clone()
-
+    
+    '''
     model = Conformer(
         num_features=params.feature_dim,
         nhead=params.nhead,
@@ -517,6 +518,14 @@ def main():
         vgg_frontend=params.vgg_frontend,
         use_feat_batchnorm=params.use_feat_batchnorm,
     )
+    '''
+    model = Transformer(
+        num_features=params.feature_dim,
+        num_classes=num_classes,
+        use_feat_batchnorm=params.use_feat_batchnorm,
+        num_encoder_layers=params.num_encoder_layers,
+        num_decoder_layers=params.num_decoder_layers,
+    )
 
     if params.avg == 1:
         load_checkpoint(f"{params.exp_dir}/epoch-{params.epoch}.pt", model)