diff --git a/hubconf.py b/hubconf.py
index 28d2c5a5d01..a229ab07667 100644
--- a/hubconf.py
+++ b/hubconf.py
@@ -1,6 +1,7 @@
 # Optional list of dependencies required by the package
 dependencies = ["torch"]
 
+from torchvision.models import get_weight
 from torchvision.models.alexnet import alexnet
 from torchvision.models.convnext import convnext_tiny, convnext_small, convnext_base, convnext_large
 from torchvision.models.densenet import densenet121, densenet169, densenet201, densenet161
diff --git a/torchvision/models/_api.py b/torchvision/models/_api.py
index 05b35fe87f0..a202ed625b5 100644
--- a/torchvision/models/_api.py
+++ b/torchvision/models/_api.py
@@ -107,7 +107,7 @@ def get_weight(name: str) -> WeightsEnum:
     return weights_enum.from_str(value_name)
 
 
-def get_enum_from_fn(fn: Callable) -> WeightsEnum:
+def _get_enum_from_fn(fn: Callable) -> WeightsEnum:
     """
     Internal method that gets the weight enum of a specific model builder method.
     Might be removed after the handle_legacy_interface is removed.
diff --git a/torchvision/models/detection/backbone_utils.py b/torchvision/models/detection/backbone_utils.py
index 65fe45c4cbd..fbef524b99c 100644
--- a/torchvision/models/detection/backbone_utils.py
+++ b/torchvision/models/detection/backbone_utils.py
@@ -6,7 +6,7 @@
 from torchvision.ops.feature_pyramid_network import ExtraFPNBlock, FeaturePyramidNetwork, LastLevelMaxPool
 
 from .. import mobilenet, resnet
-from .._api import WeightsEnum, get_enum_from_fn
+from .._api import WeightsEnum, _get_enum_from_fn
 from .._utils import IntermediateLayerGetter, handle_legacy_interface
 
 
@@ -62,7 +62,7 @@ def forward(self, x: Tensor) -> Dict[str, Tensor]:
 @handle_legacy_interface(
     weights=(
         "pretrained",
-        lambda kwargs: get_enum_from_fn(resnet.__dict__[kwargs["backbone_name"]]).from_str("IMAGENET1K_V1"),
+        lambda kwargs: _get_enum_from_fn(resnet.__dict__[kwargs["backbone_name"]]).from_str("IMAGENET1K_V1"),
     ),
 )
 def resnet_fpn_backbone(
@@ -177,7 +177,7 @@ def _validate_trainable_layers(
 @handle_legacy_interface(
     weights=(
         "pretrained",
-        lambda kwargs: get_enum_from_fn(mobilenet.__dict__[kwargs["backbone_name"]]).from_str("IMAGENET1K_V1"),
+        lambda kwargs: _get_enum_from_fn(mobilenet.__dict__[kwargs["backbone_name"]]).from_str("IMAGENET1K_V1"),
     ),
 )
 def mobilenet_backbone(