Update instructions for using with KerasCV

README.md

@@ -221,12 +221,12 @@ from targetran.tf import to_keras_cv_dict, to_keras_cv_model_input
 
 # Let's assume `ds` contains Targetran ops as in the above illustration,
 # but without batching. To map the outputs to a KerasCV preprocessing layer,
-# the following can be done to get the required data format.
+# the following can be done.
 ds = to_keras_cv_dict(ds, batch_size=2)
 
 # The resulting dataset yields batches readily to be passed to a KerasCV
-# preprocessing layer. Batching in the appropriate format is done directly 
-# with this call, therefore the `padded_batch` example is not relevant here.
+# preprocessing layer. Batching in the appropriate format will be included,
+# therefore the `padded_batch` example is not relevant here.
 
 # Assume the user would like to add a jittered-resize op.
 jittered_resize = keras_cv.layers.JitteredResize(