message: Refering to new documentation that was added
diff: This page describes how you can check the accuracy of quantized models to verify that any degradation in accuracy is within acceptable limits.
  +## Accuracy & correctness
  +TensorFlow Lite has two types of tooling to measure how accurately a delegate behaves for a given model: Task-Based and Task-Agnostic.
  +
  +For more information visit the [Tools for Evaluation](https://www.tensorflow.org/lite/performance/delegates#tools_for_evaluation) page.
  +
  ## Tools
  There are three different binaries which are supported. A brief description of each is provided below.
  ### [Inference Diff Tool](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/tools/evaluation/tasks/inference_diff#inference-diff-tool)
  This binary compares TensorFlow Lite execution in single-threaded CPU inference and user-defined inference.
  -
  -
  ### [Image Classification Evaluation](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/tools/evaluation/tasks/imagenet_image_classification#image-classification-evaluation-based-on-ilsvrc-2012-task)
  This binary evaluates TensorFlow Lite models trained for the [ILSVRC 2012 image classification task.](http://www.image-net.org/challenges/LSVRC/2012/)
  