diff --git a/ml/examples/cuda_test.rs b/ml/examples/cuda_test.rs
index de8dbd391..2fb3cfa91 100644
--- a/ml/examples/cuda_test.rs
+++ b/ml/examples/cuda_test.rs
@@ -4,7 +4,7 @@
 //! can successfully create tensors and perform basic operations.
 
 use candle_core::{Device, Tensor};
-use candle_nn::{Linear, Module, VarBuilder, VarMap};
+use candle_nn::{linear, Module, VarBuilder, VarMap};
 
 /// Test basic CUDA tensor operations
 pub fn test_cuda_basic() -> Result<(), Box<dyn std::error::Error>> {
@@ -39,14 +39,14 @@ pub fn test_cuda_neural_network() -> Result<(), Box<dyn std::error::Error>> {
 
     match Device::new_cuda(0) {
         Ok(device) => {
-            let mut varmap = VarMap::new();
+            let varmap = VarMap::new();
             let vs = VarBuilder::from_varmap(&varmap, candle_core::DType::F32, &device);
 
             // Create a simple linear layer
-            let linear = Linear::new(10, 5, vs.pp("linear"))?;
+            let linear_layer = linear(10, 5, vs.pp("linear"))?;
             let input = Tensor::randn(0f32, 1.0, (1, 10), &device)?;
 
-            let output = linear.forward(&input)?;
+            let output = linear_layer.forward(&input)?;
             println!(
                 "✅ Neural network forward pass successful: {:?}",
                 output.shape()