diff --git a/uniception/models/encoders/dinov2.py b/uniception/models/encoders/dinov2.py
index 275d4e3..df5204a 100644
--- a/uniception/models/encoders/dinov2.py
+++ b/uniception/models/encoders/dinov2.py
@@ -25,6 +25,7 @@ def __init__(
         norm_returned_features: bool = True,
         pretrained_checkpoint_path: str = None,
         torch_hub_force_reload: bool = False,
+        torch_hub_pretrained: bool = True,
         gradient_checkpointing: bool = False,
         keep_first_n_layers: Optional[int] = None,
         use_pytorch_sdpa=True,
@@ -43,6 +44,7 @@ def __init__(
             with_registers (bool): Whether to use the DINOv2 model with registers. Default: False
             pretrained_checkpoint_path (str): Path to the pretrained checkpoint if using custom trained version of DINOv2. Default: None
             torch_hub_force_reload (bool): Whether to force reload the model from torch hub. Default: False
+            torch_hub_pretrained (bool): Whether to use the pretrained weights from torch hub. Default: True
             gradient_checkpointing (bool): Whether to use gradient checkpointing to save GPU memory during backward call. Default: False
             keep_first_n_layers (Optional[int]): If specified, only the first n layers of the model will be kept. Default: None
             use_pytorch_sdpa (bool): Whether to use PyTorch native SDPA for attention layers. Default: True
@@ -90,9 +92,14 @@ def __init__(
                 "facebookresearch/dinov2",
                 DINO_MODELS[self.with_registers][self.version],
                 force_reload=torch_hub_force_reload,
+                pretrained=torch_hub_pretrained if pretrained_checkpoint_path is None else False,
             )
         except:  # Load from cache
-            self.model = torch.hub.load("facebookresearch/dinov2", DINO_MODELS[self.with_registers][self.version])
+            self.model = torch.hub.load(
+                "facebookresearch/dinov2",
+                DINO_MODELS[self.with_registers][self.version],
+                pretrained=torch_hub_pretrained if pretrained_checkpoint_path is None else False,
+            )
 
         del (
             self.model.mask_token
diff --git a/uniception/models/encoders/dune.py b/uniception/models/encoders/dune.py
index c7d1725..ffd2064 100644
--- a/uniception/models/encoders/dune.py
+++ b/uniception/models/encoders/dune.py
@@ -94,11 +94,13 @@ def __init__(
                 "facebookresearch/dinov2",
                 DINO_MODELS[self.with_registers][self.version],
                 force_reload=torch_hub_force_reload,
+                pretrained=False,
             )
         except:  # Load from cache
             self.model = torch.hub.load(
                 "facebookresearch/dinov2",
                 DINO_MODELS[self.with_registers][self.version],
+                pretrained=False,
             )
 
         del (