Fix GitHub link.

PiperOrigin-RevId: 224897071

tensorflow/lite/g3doc/convert/cmdline_examples.md

@@ -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.