message: Add Raspberry Pi section and link to github build instructions.
diff: @@ -190,7 +190,7 @@ graph visualization.
  ## 3. Use the TensorFlow Lite model for inference in a mobile app
  -After completing the prior steps, you should now have a .tflite model file.
  +After completing the prior steps, you should now have a `.tflite` model file.
  ### Android
  @@ -222,3 +222,10 @@ trained Tensorflow models to the
  [CoreML](https://developer.apple.com/machine-learning/) format for use on Apple
  devices. To use the converter, refer to the
  [Tensorflow-CoreML converter documentation](https://github.com/tf-coreml/tf-coreml).
  +
  +### Raspberry Pi
  +
  +Compile Tensorflow Lite for a Raspberry Pi by following the
  +[RPi build instructions](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/g3doc/rpi.md)
  +This compiles a static library file (`.a`) used to build your app. There are
  +plans for Python bindings and a demo app.
  