diff --git a/src/lerobot/policies/pi0/modeling_pi0.py b/src/lerobot/policies/pi0/modeling_pi0.py
index 58b5dc07b..a0263eb24 100644
--- a/src/lerobot/policies/pi0/modeling_pi0.py
+++ b/src/lerobot/policies/pi0/modeling_pi0.py
@@ -995,7 +995,14 @@ class PI0Policy(PreTrainedPolicy):
 
         # Initialize model without loading weights
         # Check if dataset_stats were provided in kwargs
-        model = cls(config, **kwargs)
+        if _transformers_available:
+            from transformers.modeling_utils import no_init_weights
+
+            with no_init_weights():
+                model = cls(config, **kwargs)
+            model.model.paligemma_with_expert.paligemma.tie_weights()
+        else:
+            model = cls(config, **kwargs)
 
         # Now manually load and remap the state dict
         try:
diff --git a/src/lerobot/policies/pi05/modeling_pi05.py b/src/lerobot/policies/pi05/modeling_pi05.py
index 3929e9ebf..2c57c4824 100644
--- a/src/lerobot/policies/pi05/modeling_pi05.py
+++ b/src/lerobot/policies/pi05/modeling_pi05.py
@@ -969,6 +969,7 @@ class PI05Policy(PreTrainedPolicy):
         # Check if dataset_stats were provided in kwargs
         if _transformers_available:
             from transformers.modeling_utils import no_init_weights
+
             with no_init_weights():
                 model = cls(config, **kwargs)
             model.model.paligemma_with_expert.paligemma.tie_weights()
diff --git a/src/lerobot/policies/pi0_fast/modeling_pi0_fast.py b/src/lerobot/policies/pi0_fast/modeling_pi0_fast.py
index b4bc7ba22..6343672a7 100644
--- a/src/lerobot/policies/pi0_fast/modeling_pi0_fast.py
+++ b/src/lerobot/policies/pi0_fast/modeling_pi0_fast.py
@@ -895,7 +895,14 @@ class PI0FastPolicy(PreTrainedPolicy):
 
         # Initialize model without loading weights
         # Check if dataset_stats were provided in kwargs
-        model = cls(config, **kwargs)
+        if _transformers_available:
+            from transformers.modeling_utils import no_init_weights
+
+            with no_init_weights():
+                model = cls(config, **kwargs)
+            model.model.paligemma_with_expert.paligemma.tie_weights()
+        else:
+            model = cls(config, **kwargs)
 
         # Now manually load and remap the state dict
         try: