diff --git a/README.md b/README.md
index 2d4ca49..86b9f69 100644
--- a/README.md
+++ b/README.md
@@ -62,10 +62,30 @@ If the system is found to have an nvidia graphics card available, and the host h
 
 To enable proper use of the GPU within docker, the nvidia runtime must be used.  By default, the nvidia runtime will be configured to use ([CDI](https://github.com/cncf-tags/container-device-interface)) mode, and a the appropriate nvidia CDI config will be automatically created for the system.  You just need to specify the nvidia runtime when running a container.
 
-Example usage:
+### Usage examples
+
+Generic example usage would look something like:
+
+```shell
+docker run --rm --runtime nvidia --gpus all {cuda-container-image-name}
+```
+
+or
 
 ```shell
-docker run --rm --runtime nvidia {cuda-container-image-name}
+docker run --rm --runtime nvidia --env NVIDIA_VISIBLE_DEVICES=all {cuda-container-image-name}
+```
+
+If your container image already has appropriate environment variables set, may be able to just specify the nvidia runtime with no additional args required.
+
+Please refer to this guide for mode detail regarding environment variables that can be used.
+
+*NOTE*: library path and discovery is automatically handled, but binary paths are not, so if you wish to test using something like `nviida-smi` you could can either specify the full path of set the PATH environment variable.
+
+e.g.
+
+```
+docker run --rm --runtime=nvidia --gpus all --env PATH="${PATH}:/var/lib/snapd/hostfs/usr/bin" ubuntu nvidia-smi
 ```
 
 ### Ubuntu Core 22