diff --git a/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp b/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp
index 4f69cecf49..6ab999eef9 100644
--- a/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp
+++ b/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp
@@ -39,6 +39,10 @@ int main(int argc, char* argv[]) {
   // 2 -> To enable all optimizations (Includes level 1 + more complex optimizations like node fusions)
   OrtSetSessionGraphOptimizationLevel(session_options, 1);
 
+  // Optionally add more execution providers via session_options
+  // E.g. for CUDA include cuda_provider_factory.h and uncomment the following line:
+  // OrtSessionOptionsAppendExecutionProvider_CUDA(sessionOptions, 0);
+
   //*************************************************************************
   // create session and load model into memory
   // using squeezenet version 1.3
diff --git a/docs/C_API.md b/docs/C_API.md
index dc166fad81..e13ddecfb0 100644
--- a/docs/C_API.md
+++ b/docs/C_API.md
@@ -5,9 +5,9 @@
 * Creating an InferenceSession from an on-disk model file and a set of SessionOptions.
 * Registering customized loggers.
 * Registering customized allocators.
-* Registering predefined providers and set the priority order. ONNXRuntime has a set of predefined execution providers,like CUDA, MKLDNN. User can register providers to their InferenceSession. The order of registration indicates the preference order as well.
+* Registering predefined providers and set the priority order. ONNXRuntime has a set of predefined execution providers, like CUDA, MKLDNN. User can register providers to their InferenceSession. The order of registration indicates the preference order as well.
 * Running a model with inputs. These inputs must be in CPU memory, not GPU. If the model has multiple outputs, user can specify which outputs they want.
-* Converting an in-memory ONNX Tensor encoded in protobuf format, to a pointer that can be used as model input.
+* Converting an in-memory ONNX Tensor encoded in protobuf format to a pointer that can be used as model input.
 * Setting the thread pool size for each session.
 * Setting graph optimization level for each session.
 * Dynamically loading custom ops. [Instructions](/docs/AddingCustomOp.md)
@@ -17,6 +17,7 @@
 1. Include [onnxruntime_c_api.h](/include/onnxruntime/core/session/onnxruntime_c_api.h).
 2. Call OrtCreateEnv
 3. Create Session: OrtCreateSession(env, model_uri, nullptr,...)
+   - Optionally add more execution providers (e.g. for CUDA use OrtSessionOptionsAppendExecutionProvider_CUDA)
 4. Create Tensor
    1) OrtCreateAllocatorInfo
    2) OrtCreateTensorWithDataAsOrtValue
@@ -24,7 +25,6 @@
 
 ## Sample code
 
-The example below shows a sample run using the SqueezeNet model from ONNX model zoo, including dynamically reading model inputs, outputs, shape and type information, as well as running a sample vector and fetching the resulting class probabilities for inspection. 
+The example below shows a sample run using the SqueezeNet model from ONNX model zoo, including dynamically reading model inputs, outputs, shape and type information, as well as running a sample vector and fetching the resulting class probabilities for inspection.
 
 * [../csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp](../csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp)
-