diff --git a/examples/inception_v3/inception_v3.cpp b/examples/inception_v3/inception_v3.cpp
new file mode 100644
index 0000000..9c8e0db
--- /dev/null
+++ b/examples/inception_v3/inception_v3.cpp
@@ -0,0 +1,48 @@
+#include <cudanet.cuh>
+#include <iostream>
+
+int main(int argc, const char *const argv[]) {
+    if (argc != 3) {
+        std::cerr << "Usage: " << argv[0] << "<model_weights_path> <image_path>"
+                  << std::endl;
+        return 1;  // Return error code indicating incorrect usage
+    }
+
+    std::cout << "Loading model..." << std::endl;
+}
+
+class BasicConv2d : public CUDANet::Module {
+  public:
+    BasicConv2d(
+        const int inputSize,
+        const int inputChannels,
+        const int outputChannels,
+        const int kernelSize,
+        const int stride,
+        const int padding,
+        const std::string& prefix
+    )
+        : inputSize(inputSize),
+          inputChannels(inputChannels),
+          outputChannels(outputChannels) {
+        // Create the convolution layer
+        CUDANet::Layers::Conv2d *conv = new CUDANet::Layers::Conv2d(
+            inputSize, inputChannels, kernelSize, stride, outputChannels, padding, CUDANet::Layers::ActivationType::NONE
+        );
+
+        int batchNormSize = conv->getOutputSize();
+
+        CUDANet::Layers::BatchNorm *batchNorm =
+            new CUDANet::Layers::BatchNorm(
+                batchNormSize, outputChannels, 1e-3f, CUDANet::Layers::ActivationType::RELU
+            );
+
+        addLayer(prefix + ".conv", conv);
+        addLayer(prefix + ".bn", batchNorm);
+    }
+
+  private:
+    int inputSize;
+    int inputChannels;
+    int outputChannels;
+};
diff --git a/examples/inception_v3/inception_v3.py b/examples/inception_v3/inception_v3.py
new file mode 100644
index 0000000..0570af7
--- /dev/null
+++ b/examples/inception_v3/inception_v3.py
@@ -0,0 +1,17 @@
+import torch
+import torchvision
+import sys
+
+from torchsummary import summary
+
+inception = torchvision.models.inception_v3(weights=torchvision.models.Inception_V3_Weights.DEFAULT)
+inception.eval()
+
+sys.path.append('../../tools')  # Ugly hack 
+from utils import export_model_weights, print_model_parameters
+
+print_model_parameters(inception)  # print layer names and number of parameters
+
+inception.cuda()
+
+summary(inception, (3, 299, 299))
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