diff --git a/tensorflow/lite/g3doc/models/image_classification/overview.md b/tensorflow/lite/g3doc/models/image_classification/overview.md
index 9ddbaf43ef0..e02e96f5c1f 100644
--- a/tensorflow/lite/g3doc/models/image_classification/overview.md
+++ b/tensorflow/lite/g3doc/models/image_classification/overview.md
@@ -22,8 +22,10 @@ We also provide <a href="example_applications">example applications</a> you can
 use to get started.
 
 If you are using a platform other than Android or iOS, or you are already
-familiar with the <a href="https://www.tensorflow.org/api_docs/python/tf/lite">TensorFlow Lite APIs</a>, you can
-download our starter image classification model and the accompanying labels.
+familiar with the
+<a href="https://www.tensorflow.org/api_docs/python/tf/lite">TensorFlow Lite
+APIs</a>, you can download our starter image classification model and the
+accompanying labels.
 
 <a class="button button-primary" href="https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_1.0_224_quant_and_labels.zip">Download
 starter model and labels</a>
@@ -33,13 +35,6 @@ experiment with different models to find the optimal balance between
 performance, accuracy, and model size. For guidance, see
 <a href="#choose_a_different_model">Choose a different model</a>.
 
-If you are using a platform other than Android or iOS, or you are already
-familiar with the <a href="https://www.tensorflow.org/api_docs/python/tf/lite">TensorFlow Lite APIs</a>, you can
-download our starter image classification model and the accompanying labels.
-
-<a class="button button-primary" href="https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_1.0_224_quant_and_labels.zip">Download
-starter model and labels</a>
-
 ### Example applications
 
 We have example applications for image classification for both Android and iOS.
@@ -216,9 +211,9 @@ performance, accuracy, and model size. For guidance, see
 ## Choose a different model
 
 There are a large number of image classification models available on our
-<a href="../../guide/hosted_models.md">List of hosted models</a>. You should aim to choose the
-optimal model for your application based on performance, accuracy and model
-size. There are trade-offs between each of them.
+<a href="../../guide/hosted_models.md">List of hosted models</a>. You should aim
+to choose the optimal model for your application based on performance, accuracy
+and model size. There are trade-offs between each of them.
 
 ### Performance
 
@@ -239,11 +234,11 @@ We measure accuracy in terms of how often the model correctly classifies an
 image. For example, a model with a stated accuracy of 60% can be expected to
 classify an image correctly an average of 60% of the time.
 
-Our <a href="../../guide/hosted_models.md">list of hosted models</a> provides Top-1 and Top-5
-accuracy statistics. Top-1 refers to how often the correct label appears as the
-label with the highest probability in the model’s output. Top-5 refers to how
-often the correct label appears in the top 5 highest probabilities in the
-model’s output.
+Our <a href="../../guide/hosted_models.md">list of hosted models</a> provides
+Top-1 and Top-5 accuracy statistics. Top-1 refers to how often the correct label
+appears as the label with the highest probability in the model’s output. Top-5
+refers to how often the correct label appears in the top 5 highest probabilities
+in the model’s output.
 
 Our quantized Mobilenet models’ Top-5 accuracy ranges from 64.4 to 89.9%.
 
@@ -258,8 +253,9 @@ Our quantized Mobilenet models’ size ranges from 0.5 to 3.4 Mb.
 ### Architecture
 
 There are several different architectures of models available on
-<a href="../../guide/hosted_models.md">List of hosted models</a>, indicated by the model’s name.
-For example, you can choose between Mobilenet, Inception, and others.
+<a href="../../guide/hosted_models.md">List of hosted models</a>, indicated by
+the model’s name. For example, you can choose between Mobilenet, Inception, and
+others.
 
 The architecture of a model impacts its performance, accuracy, and size. All of
 our hosted models are trained on the same data, meaning you can use the provided