diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode_new.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode_new.py.swp
index 088947886..3014e32d7 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode_new.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode_new.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode_new.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode_new.py
index 87f3d813e..671edd23c 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode_new.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode_new.py
@@ -666,6 +666,22 @@ def main():
     
     if '.pt' in params.model_name:
         load_checkpoint(f"{params.exp_dir}/{params.model_name}", model)
+    elif 'lora' in params.model_name:
+        load_checkpoint(f"{params.exp_dir}/../d2v-base-T.pt", model)
+
+        ## for lora hooking
+        lora_modules = []
+        for modules in model.modules():
+            if isinstance(modules, fairseq.modules.multihead_attention.MultiheadAttention):
+                for module in modules.modules():
+                    if isinstance(module, torch.nn.Linear):
+                        lora_modules.append(LoRAHook(module))
+
+        for i, lora in enumerate(lora_modules):
+            lora_param = torch.load(f"{params.exp_dir}/lora_{params.iter}_{i}.pt")
+            lora.lora.load_state_dict(lora_param)
+            lora.lora.to(device)
+        logging.info("lora params load done")
     else:
         if not params.use_averaged_model:
             if params.iter > 0: