diff --git a/brainscore_vision/models/resnet_50_pytorch/__init__.py b/brainscore_vision/models/resnet_50_pytorch/__init__.py
new file mode 100644
index 000000000..0953620e8
--- /dev/null
+++ b/brainscore_vision/models/resnet_50_pytorch/__init__.py
@@ -0,0 +1,7 @@
+from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
+from brainscore_vision import model_registry
+from .model import get_layers,get_model
+
+
+model_registry['resnet-50-pytorch'] = \
+    lambda: ModelCommitment(identifier='resnet-50-pytorch', activations_model=get_model('resnet-50-pytorch'), layers=get_layers('resnet-50-pytorch'))
\ No newline at end of file
diff --git a/brainscore_vision/models/resnet_50_pytorch/model.py b/brainscore_vision/models/resnet_50_pytorch/model.py
new file mode 100644
index 000000000..0a84b29ce
--- /dev/null
+++ b/brainscore_vision/models/resnet_50_pytorch/model.py
@@ -0,0 +1,66 @@
+import functools
+from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
+from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
+from brainscore_vision.model_helpers.check_submission import check_models
+import torchvision
+from importlib import import_module
+
+model = torchvision.models.resnet50(weights='DEFAULT')
+
+
+def get_model(name):
+    """
+    This method fetches an instance of a base model. The instance has to be callable and return a xarray object,
+    containing activations. There exist standard wrapper implementations for common libraries, like pytorch and
+    keras. Checkout the examples folder, to see more. For custom implementations check out the implementation of the
+    wrappers.
+    :param name: the name of the model to fetch
+    :return: the model instance
+    """
+    assert name == 'resnet-50-pytorch'
+    module = import_module(f'torchvision.models')
+    model_ctr = getattr(module, "resnet50")
+    preprocessing = functools.partial(load_preprocess_images, image_size=224)
+    wrapper = PytorchWrapper(identifier=name, model=model_ctr(pretrained=True), preprocessing=preprocessing)
+    wrapper.image_size = 224
+    return wrapper
+
+
+def get_layers(name):
+    assert name == 'resnet-50-pytorch'
+    layers = ['conv1', 'layer1.0.conv3', 'layer1.1.conv3', 'layer1.2.conv3',
+              'layer2.0.downsample.0', 'layer2.1.conv3', 'layer2.2.conv3', 'layer2.3.conv3',
+              'layer3.0.downsample.0', 'layer3.1.conv3', 'layer3.2.conv3', 'layer3.3.conv3',
+              'layer3.4.conv3', 'layer3.5.conv3',
+              'layer4.0.downsample.0', 'layer4.1.conv3', 'layer4.2.conv3', 'avgpool']
+    return layers
+
+
+def get_bibtex(model_identifier):
+    """
+    A method returning the bibtex reference of the requested model as a string.
+    """
+    return '''
+@article{DBLP:journals/corr/HeZRS15,
+  author       = {Kaiming He and
+                  Xiangyu Zhang and
+                  Shaoqing Ren and
+                  Jian Sun},
+  title        = {Deep Residual Learning for Image Recognition},
+  journal      = {CoRR},
+  volume       = {abs/1512.03385},
+  year         = {2015},
+  url          = {http://arxiv.org/abs/1512.03385},
+  eprinttype    = {arXiv},
+  eprint       = {1512.03385},
+  timestamp    = {Wed, 25 Jan 2023 11:01:16 +0100},
+  biburl       = {https://dblp.org/rec/journals/corr/HeZRS15.bib},
+  bibsource    = {dblp computer science bibliography, https://dblp.org}
+}
+'''
+
+
+if __name__ == '__main__':
+    # Use this method to ensure the correctness of the BaseModel implementations.
+    # It executes a mock run of brain-score benchmarks.
+    check_models.check_base_models(__name__)
diff --git a/brainscore_vision/models/resnet_50_pytorch/region_layer_map/resnet-50-pytorch.json b/brainscore_vision/models/resnet_50_pytorch/region_layer_map/resnet-50-pytorch.json
new file mode 100644
index 000000000..073cc7a88
--- /dev/null
+++ b/brainscore_vision/models/resnet_50_pytorch/region_layer_map/resnet-50-pytorch.json
@@ -0,0 +1,6 @@
+{
+    "V1": "layer3.0.downsample.0",
+    "V2": "layer3.0.downsample.0",
+    "V4": "layer3.0.downsample.0",
+    "IT": "layer4.0.downsample.0"
+}
\ No newline at end of file
diff --git a/brainscore_vision/models/resnet_50_pytorch/requirements.txt b/brainscore_vision/models/resnet_50_pytorch/requirements.txt
new file mode 100644
index 000000000..abf50367e
--- /dev/null
+++ b/brainscore_vision/models/resnet_50_pytorch/requirements.txt
@@ -0,0 +1 @@
+torchvision
\ No newline at end of file
diff --git a/brainscore_vision/models/resnet_50_pytorch/test.py b/brainscore_vision/models/resnet_50_pytorch/test.py
new file mode 100644
index 000000000..a80fb3d1e
--- /dev/null
+++ b/brainscore_vision/models/resnet_50_pytorch/test.py
@@ -0,0 +1,9 @@
+import brainscore_vision
+import pytest
+
+
+
+@pytest.mark.travis_slow
+def test_has_identifier():
+    model = brainscore_vision.load_model('resnet-50-pytorch')
+    assert model.identifier == 'resnet-50-pytorch'
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