Documentation for Task library demos

PiperOrigin-RevId: 335447818
Change-Id: Iaab7231b45b6b240063947a6b89a895844c0f154

tensorflow/lite/g3doc/inference_with_metadata/task_library/image_classifier.md

@@ -50,6 +50,10 @@ API.
 
 ## Run inference in Java
 
+See the
+[Image Classification reference app](https://github.com/tensorflow/examples/blob/master/lite/examples/image_classification/android/EXPLORE_THE_CODE.md)
+for an example of how to use `ImageClassifier` in an Android app.
+
 ### Step 1: Import Gradle dependency and other settings
 
 Copy the `.tflite` model file to the assets directory of the Android module

tensorflow/lite/g3doc/inference_with_metadata/task_library/nl_classifier.md

@@ -29,6 +29,10 @@ API.
 
 ## Run inference in Java
 
+See the
+[Text Classification reference app](https://github.com/tensorflow/examples/blob/master/lite/examples/text_classification/android/lib_task_api/src/main/java/org/tensorflow/lite/examples/textclassification/client/TextClassificationClient.java)
+for an example of how to use `NLClassifier` in an Android app.
+
 ### Step 1: Import Gradle dependency and other settings
 
 Copy the `.tflite` model file to the assets directory of the Android module

tensorflow/lite/g3doc/models/image_classification/overview.md

@@ -34,6 +34,18 @@ For each example, we provide a guide that explains how it works.
 
 #### Android
 
+You can leverage the out-of-box API from TensorFlow Lite Task Library to
+[integrate image classification models](../../inference_with_metadata/task_library/image_classifier)
+in just a few lines of code. You can also
+[build your own custom inference pipleline](../../inference_with_metadata/lite_support)
+using the TensorFlow Lite Support Library.
+
+The Android example below demonstrates the implementation for both methods as
+[lib_task_api](https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android/lib_task_api)
+and
+[lib_support](https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android/lib_support),
+respectively.
+
 <a class="button button-primary" href="https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android">View
 Android example</a>
 

tensorflow/lite/g3doc/models/text_classification/overview.md

@@ -7,7 +7,16 @@ Use a pre-trained model to category a paragraph into predefined groups.
 <img src="images/screenshot.gif" class="attempt-right" style="max-width: 300px">
 
 If you are new to TensorFlow Lite and are working with Android, we recommend
-exploring the following example applications that can help you get started.
+exploring the guide of TensorFLow Lite Task Library to
+[integrate text classification models](../../inference_with_metadata/task_library/nl_classifier).
+within just a few lines of code. You can also integrate the model using the
+[TensorFlow Lite Interpreter Java API](../../guide/inference#load_and_run_a_model_in_java).
+
+The Android example below demonstrates the implementation for both methods as
+[lib_task_api](https://github.com/tensorflow/examples/tree/master/lite/examples/text_classification/android/lib_task_api)
+and
+[lib_interpreter](https://github.com/tensorflow/examples/tree/master/lite/examples/text_classification/android/lib_interpreter),
+respectively.
 
 <a class="button button-primary" href="https://github.com/tensorflow/examples/tree/master/lite/examples/text_classification/android">Android
 example</a>

tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb

@@ -59,6 +59,9 @@
         "  \u003ctd\u003e\n",
         "    \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/tensorflow/tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
         "  \u003c/td\u003e\n",
+        "  \u003ctd\u003e\n",
+        "    \u003ca href=\"https://tfhub.dev/\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/hub_logo_32px.png\" /\u003eSee TF Hub model\u003c/a\u003e\n",
+        "  \u003c/td\u003e\n",
         "\u003c/table\u003e"
       ]
     },
@@ -745,7 +748,7 @@
         "id": "ROS2Ay2jMPCl"
       },
       "source": [
-        "The TensorFlow Lite model file could be used in [image classification](https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification) reference app using [TensorFlow Lite Android wrapper code generator](https://www.tensorflow.org/lite/inference_with_metadata/codegen#generate_code_with_tensorflow_lite_android_code_generator). Thus, we could run the retrained float TensorFlow Lite model on the android app."
+        "See [example applications and guides of image classification](https://www.tensorflow.org/lite/models/image_classification/overview#example_applications_and_guides) for more details about how to integrate the TensorFlow Lite model into mobile apps."
       ]
     },
     {