diff --git a/docsrc/user_guide/saving_models.rst b/docsrc/user_guide/saving_models.rst
index 42cff7b954..dc4b5da222 100644
--- a/docsrc/user_guide/saving_models.rst
+++ b/docsrc/user_guide/saving_models.rst
@@ -34,7 +34,7 @@ Here's an example usage
     model = MyModel().eval().cuda()
     inputs = [torch.randn((1, 3, 224, 224)).cuda()]
     # trt_ep is a torch.fx.GraphModule object
-    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs) 
+    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs=inputs)
     torch_tensorrt.save(trt_gm, "trt.ep", inputs=inputs)
 
     # Later, you can load it and run inference
@@ -52,7 +52,7 @@ b) Torchscript
     model = MyModel().eval().cuda()
     inputs = [torch.randn((1, 3, 224, 224)).cuda()]
     # trt_gm is a torch.fx.GraphModule object
-    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs)
+    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs=inputs)
     torch_tensorrt.save(trt_gm, "trt.ts", output_format="torchscript", inputs=inputs)
 
     # Later, you can load it and run inference
@@ -73,7 +73,7 @@ For `ir=ts`, this behavior stays the same in 2.X versions as well.
 
   model = MyModel().eval().cuda()
   inputs = [torch.randn((1, 3, 224, 224)).cuda()]
-  trt_ts = torch_tensorrt.compile(model, ir="ts", inputs) # Output is a ScriptModule object
+  trt_ts = torch_tensorrt.compile(model, ir="ts", inputs=inputs) # Output is a ScriptModule object
   torch.jit.save(trt_ts, "trt_model.ts")
 
   # Later, you can load it and run inference