diff --git a/brainscore_vision/models/barlow_twins_custom/__init__.py b/brainscore_vision/models/barlow_twins_custom/__init__.py
new file mode 100644
index 000000000..e47ab5797
--- /dev/null
+++ b/brainscore_vision/models/barlow_twins_custom/__init__.py
@@ -0,0 +1,5 @@
+from brainscore_vision import model_registry
+from .model import get_model
+
+# Register the Barlow Twins model with custom weights
+model_registry['barlow_twins_custom'] = lambda: get_model('barlow_twins_custom')
diff --git a/brainscore_vision/models/barlow_twins_custom/model.py b/brainscore_vision/models/barlow_twins_custom/model.py
new file mode 100644
index 000000000..496376228
--- /dev/null
+++ b/brainscore_vision/models/barlow_twins_custom/model.py
@@ -0,0 +1,44 @@
+import torch
+from pathlib import Path
+from torchvision.models import resnet18
+from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
+from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
+from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
+from brainscore_vision.model_helpers.check_submission import check_models
+from collections import OrderedDict
+from urllib.request import urlretrieve
+import functools
+
+# Custom model loader
+def get_model(name):
+    assert name == 'barlow_twins_custom'
+
+    url = " https://www.dropbox.com/scl/fi/db5yp3hols5sucujanimx/barlow_twins_weights.pth?rlkey=nalge9jixfeqorazwu4xqdbd8&st=yqf3qkaj&dl=1"
+    fh = urlretrieve(url)
+    state_dict = torch.load(fh[0], map_location=torch.device("cpu"))
+    model = resnet18(pretrained=False)
+    model.load_state_dict(state_dict, strict=False)
+    print(model)
+    preprocessing = functools.partial(load_preprocess_images, image_size=224)
+
+    activations_model = PytorchWrapper(identifier='barlow_twins_custom', model=model, preprocessing=preprocessing)
+
+    
+    return ModelCommitment(
+        identifier='barlow_twins_custom',
+        activations_model=activations_model,
+        layers=['layer1', 'layer2', 'layer3', 'layer4', 'avgpool']
+    )
+
+def get_model_list():
+    return ['barlow_twins_custom']
+
+# Specify layers to test
+def get_layers(name):
+    assert name == 'barlow_twins_custom'
+    return ['layer1', 'layer2', 'layer3', 'layer4', 'avgpool']
+
+
+if __name__ == '__main__':
+
+    check_models.check_base_models(__name__)
diff --git a/brainscore_vision/models/barlow_twins_custom/requirements.txt b/brainscore_vision/models/barlow_twins_custom/requirements.txt
new file mode 100644
index 000000000..4feb6a389
--- /dev/null
+++ b/brainscore_vision/models/barlow_twins_custom/requirements.txt
@@ -0,0 +1,5 @@
+torch
+torchvision
+requests
+pathlib
+urlretrieve
\ No newline at end of file
diff --git a/brainscore_vision/models/barlow_twins_custom/test.py b/brainscore_vision/models/barlow_twins_custom/test.py
new file mode 100644
index 000000000..d9576c644
--- /dev/null
+++ b/brainscore_vision/models/barlow_twins_custom/test.py
@@ -0,0 +1,12 @@
+import pytest
+import brainscore_vision
+
+@pytest.mark.travis_slow
+def test_barlow_twins_custom():
+    model = brainscore_vision.load_model('barlow_twins_custom')
+    assert model.identifier == 'barlow_twins_custom'
+
+
+
+# AssertionError: No registrations found for resnet18_random
+# ⚡ master ~/vision python -m brainscore_vision score --model_identifier='resnet50_tutorial' --benchmark_identifier='MajajHong2015public.IT-pls'
\ No newline at end of file