diff --git a/dquartic/model/diffusion_model.py b/dquartic/model/diffusion_model.py
new file mode 100644
index 0000000..70430d4
--- /dev/null
+++ b/dquartic/model/diffusion_model.py
@@ -0,0 +1,30 @@
+import torch
+import torch.nn as nn
+
+class SimpleDiffusionModel(nn.Module):
+    def __init__(self, input_dim=100, hidden_dim=256):
+        super(SimpleDiffusionModel, self).__init__()
+        self.network = nn.Sequential(
+            nn.Linear(input_dim, hidden_dim),
+            nn.ReLU(),
+            nn.Linear(hidden_dim, input_dim)
+        )
+    
+    def forward(self, x, t):
+        """
+        Args:
+            x (torch.Tensor): Input spectra (batch_size, input_dim)
+            t (torch.Tensor): Diffusion timestep (batch_size,)
+        Returns:
+            torch.Tensor: Denoised spectra
+        """
+        return self.network(x)
+
+if __name__ == "__main__":
+    # Test the model with simulated DIA-MS/MS data
+    model = SimpleDiffusionModel()
+    noisy_spectra = torch.randn(32, 100)  # Batch of 32 spectra, 100 features
+    timestep = torch.ones(32)             # Dummy timestep
+    denoised_spectra = model(noisy_spectra, timestep)
+    print("Input shape:", noisy_spectra.shape)
+    print("Output shape:", denoised_spectra.shape)
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