Add Raspberry Pi section and link to github build instructions.

PiperOrigin-RevId: 191807862

diff --git a/tensorflow/docs_src/mobile/tflite/devguide.md b/tensorflow/docs_src/mobile/tflite/devguide.md
index 96392a3..4133bc1 100644 (file)
--- a/tensorflow/docs_src/mobile/tflite/devguide.md
+++ b/tensorflow/docs_src/mobile/tflite/devguide.md
@@ -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.