diff --git a/docs/source/models/resnext.rst b/docs/source/models/resnext.rst
index b2b0eb8694f..7dd6126c8c7 100644
--- a/docs/source/models/resnext.rst
+++ b/docs/source/models/resnext.rst
@@ -10,7 +10,7 @@ paper.
 Model builders
 --------------
 
-The following model builders can be used to instantiate an ResNext model, with or
+The following model builders can be used to instantiate a ResNext model, with or
 without pre-trained weights. All the model builders internally rely on the
 ``torchvision.models.resnet.ResNet`` base class. Please refer to the `source
 code
diff --git a/docs/source/models/wide_resnet.rst b/docs/source/models/wide_resnet.rst
new file mode 100644
index 00000000000..9768355c77e
--- /dev/null
+++ b/docs/source/models/wide_resnet.rst
@@ -0,0 +1,25 @@
+Wide ResNet
+===========
+
+.. currentmodule:: torchvision.models
+
+The Wide ResNet model is based on the `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`__
+paper.
+
+
+Model builders
+--------------
+
+The following model builders can be used to instantiate a Wide ResNet model, with or
+without pre-trained weights. All the model builders internally rely on the
+``torchvision.models.resnet.ResNet`` base class. Please refer to the `source
+code
+<https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_ for
+more details about this class.
+
+.. autosummary::
+    :toctree: generated/
+    :template: function.rst
+
+    wide_resnet50_2
+    wide_resnet101_2
diff --git a/docs/source/models_new.rst b/docs/source/models_new.rst
index c1b7e04339c..f9aa889c383 100644
--- a/docs/source/models_new.rst
+++ b/docs/source/models_new.rst
@@ -50,6 +50,7 @@ weights:
    models/swin_transformer
    models/vgg
    models/vision_transformer
+   models/wide_resnet
 
 
 Table of all available classification weights
diff --git a/torchvision/models/resnet.py b/torchvision/models/resnet.py
index 3c71938fa1d..dad745f2c8d 100644
--- a/torchvision/models/resnet.py
+++ b/torchvision/models/resnet.py
@@ -738,8 +738,8 @@ def resnext101_32x8d(
 def wide_resnet50_2(
     *, weights: Optional[Wide_ResNet50_2_Weights] = None, progress: bool = True, **kwargs: Any
 ) -> ResNet:
-    r"""Wide ResNet-50-2 model from
-    `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_.
+    """Wide ResNet-50-2 model from
+    `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
 
     The model is the same as ResNet except for the bottleneck number of channels
     which is twice larger in every block. The number of channels in outer 1x1
@@ -747,8 +747,19 @@ def wide_resnet50_2(
     channels, and in Wide ResNet-50-2 has 2048-1024-2048.
 
     Args:
-        weights (Wide_ResNet50_2_Weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
+        weights (:class:`~torchvision.models.Wide_ResNet50_2_Weights`, optional): The
+            pretrained weights to use. See
+            :class:`~torchvision.models.Wide_ResNet50_2_Weights` below for
+            more details, and possible values. By default, no pre-trained
+            weights are used.
+        progress (bool, optional): If True, displays a progress bar of the
+            download to stderr. Default is True.
+        **kwargs: parameters passed to the ``torchvision.models.resnet.ResNet``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_
+            for more details about this class.
+    .. autoclass:: torchvision.models.Wide_ResNet50_2_Weights
+        :members:
     """
     weights = Wide_ResNet50_2_Weights.verify(weights)
 
@@ -760,8 +771,8 @@ def wide_resnet50_2(
 def wide_resnet101_2(
     *, weights: Optional[Wide_ResNet101_2_Weights] = None, progress: bool = True, **kwargs: Any
 ) -> ResNet:
-    r"""Wide ResNet-101-2 model from
-    `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_.
+    """Wide ResNet-101-2 model from
+    `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
 
     The model is the same as ResNet except for the bottleneck number of channels
     which is twice larger in every block. The number of channels in outer 1x1
@@ -769,8 +780,19 @@ def wide_resnet101_2(
     channels, and in Wide ResNet-50-2 has 2048-1024-2048.
 
     Args:
-        weights (Wide_ResNet101_2_Weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
+        weights (:class:`~torchvision.models.Wide_ResNet101_2_Weights`, optional): The
+            pretrained weights to use. See
+            :class:`~torchvision.models.Wide_ResNet101_2_Weights` below for
+            more details, and possible values. By default, no pre-trained
+            weights are used.
+        progress (bool, optional): If True, displays a progress bar of the
+            download to stderr. Default is True.
+        **kwargs: parameters passed to the ``torchvision.models.resnet.ResNet``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_
+            for more details about this class.
+    .. autoclass:: torchvision.models.Wide_ResNet101_2_Weights
+        :members:
     """
     weights = Wide_ResNet101_2_Weights.verify(weights)