message: Fix GitHub link.
diff: @@ -95,11 +95,11 @@ tflite_convert \
  The TensorFlow Lite Converter is compatible with fixed point quantization models
  described
  -[here](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/q
  -uantize/README.md). These are float models with `FakeQuant*` ops inserted at the
  -boundaries of fused layers to record min-max range information. This generates a
  -quantized inference workload that reproduces the quantization behavior that was
  -used during training.
  +[here](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/quantize/README.md).
  +These are float models with `FakeQuant*` ops inserted at the boundaries of fused
  +layers to record min-max range information. This generates a quantized inference
  +workload that reproduces the quantization behavior that was used during
  +training.
  The following command generates a quantized TensorFlow Lite FlatBuffer from a
  "quantized" TensorFlow GraphDef.
  