diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp
index 492e84d93..0adc33fae 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py
index 4e2efd6c0..cbfe5ac34 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py
@@ -659,83 +659,86 @@ def main():
 
     logging.info("About to create model")
     model = get_transducer_model(params)
-
-    if not params.use_averaged_model:
-        if params.iter > 0:
-            filenames = find_checkpoints(params.exp_dir, iteration=-params.iter)[
-                : params.avg
-            ]
-            if len(filenames) == 0:
-                raise ValueError(
-                    f"No checkpoints found for"
-                    f" --iter {params.iter}, --avg {params.avg}"
-                )
-            elif len(filenames) < params.avg:
-                raise ValueError(
-                    f"Not enough checkpoints ({len(filenames)}) found for"
-                    f" --iter {params.iter}, --avg {params.avg}"
-                )
-            logging.info(f"averaging {filenames}")
-            model.to(device)
-            model.load_state_dict(average_checkpoints(filenames, device=device))
-        elif params.avg == 1:
-            load_checkpoint(f"{params.exp_dir}/epoch-{params.epoch}.pt", model)
-        else:
-            start = params.epoch - params.avg + 1
-            filenames = []
-            for i in range(start, params.epoch + 1):
-                if i >= 1:
-                    filenames.append(f"{params.exp_dir}/epoch-{i}.pt")
-            logging.info(f"averaging {filenames}")
-            model.to(device)
-            model.load_state_dict(average_checkpoints(filenames, device=device))
+    
+    if params.model_path:
+        load_checkpoint(f"{params.exp_dir}/epoch-{params.epoch}.pt", model)
     else:
-        if params.iter > 0:
-            filenames = find_checkpoints(params.exp_dir, iteration=-params.iter)[
-                : params.avg + 1
-            ]
-            if len(filenames) == 0:
-                raise ValueError(
-                    f"No checkpoints found for"
-                    f" --iter {params.iter}, --avg {params.avg}"
-                )
-            elif len(filenames) < params.avg + 1:
-                raise ValueError(
-                    f"Not enough checkpoints ({len(filenames)}) found for"
-                    f" --iter {params.iter}, --avg {params.avg}"
-                )
-            filename_start = filenames[-1]
-            filename_end = filenames[0]
-            logging.info(
-                "Calculating the averaged model over iteration checkpoints"
-                f" from {filename_start} (excluded) to {filename_end}"
-            )
-            model.to(device)
-            model.load_state_dict(
-                average_checkpoints_with_averaged_model(
-                    filename_start=filename_start,
-                    filename_end=filename_end,
-                    device=device,
-                )
-            )
+        if not params.use_averaged_model:
+            if params.iter > 0:
+                filenames = find_checkpoints(params.exp_dir, iteration=-params.iter)[
+                    : params.avg
+                ]
+                if len(filenames) == 0:
+                    raise ValueError(
+                        f"No checkpoints found for"
+                        f" --iter {params.iter}, --avg {params.avg}"
+                    )
+                elif len(filenames) < params.avg:
+                    raise ValueError(
+                        f"Not enough checkpoints ({len(filenames)}) found for"
+                        f" --iter {params.iter}, --avg {params.avg}"
+                    )
+                logging.info(f"averaging {filenames}")
+                model.to(device)
+                model.load_state_dict(average_checkpoints(filenames, device=device))
+            elif params.avg == 1:
+                load_checkpoint(f"{params.exp_dir}/epoch-{params.epoch}.pt", model)
+            else:
+                start = params.epoch - params.avg + 1
+                filenames = []
+                for i in range(start, params.epoch + 1):
+                    if i >= 1:
+                        filenames.append(f"{params.exp_dir}/epoch-{i}.pt")
+                logging.info(f"averaging {filenames}")
+                model.to(device)
+                model.load_state_dict(average_checkpoints(filenames, device=device))
         else:
-            assert params.avg > 0, params.avg
-            start = params.epoch - params.avg
-            assert start >= 1, start
-            filename_start = f"{params.exp_dir}/epoch-{start}.pt"
-            filename_end = f"{params.exp_dir}/epoch-{params.epoch}.pt"
-            logging.info(
-                f"Calculating the averaged model over epoch range from "
-                f"{start} (excluded) to {params.epoch}"
-            )
-            model.to(device)
-            model.load_state_dict(
-                average_checkpoints_with_averaged_model(
-                    filename_start=filename_start,
-                    filename_end=filename_end,
-                    device=device,
+            if params.iter > 0:
+                filenames = find_checkpoints(params.exp_dir, iteration=-params.iter)[
+                    : params.avg + 1
+                ]
+                if len(filenames) == 0:
+                    raise ValueError(
+                        f"No checkpoints found for"
+                        f" --iter {params.iter}, --avg {params.avg}"
+                    )
+                elif len(filenames) < params.avg + 1:
+                    raise ValueError(
+                        f"Not enough checkpoints ({len(filenames)}) found for"
+                        f" --iter {params.iter}, --avg {params.avg}"
+                    )
+                filename_start = filenames[-1]
+                filename_end = filenames[0]
+                logging.info(
+                    "Calculating the averaged model over iteration checkpoints"
+                    f" from {filename_start} (excluded) to {filename_end}"
+                )
+                model.to(device)
+                model.load_state_dict(
+                    average_checkpoints_with_averaged_model(
+                        filename_start=filename_start,
+                        filename_end=filename_end,
+                        device=device,
+                    )
+                )
+            else:
+                assert params.avg > 0, params.avg
+                start = params.epoch - params.avg
+                assert start >= 1, start
+                filename_start = f"{params.exp_dir}/epoch-{start}.pt"
+                filename_end = f"{params.exp_dir}/epoch-{params.epoch}.pt"
+                logging.info(
+                    f"Calculating the averaged model over epoch range from "
+                    f"{start} (excluded) to {params.epoch}"
+                )
+                model.to(device)
+                model.load_state_dict(
+                    average_checkpoints_with_averaged_model(
+                        filename_start=filename_start,
+                        filename_end=filename_end,
+                        device=device,
+                    )
                 )
-            )
 
     model.to(device)
     model.eval()