add clarification for create a recipe enablement in user guide

Author: markurtz

src/content/user-guide/recipes/enabling.mdx

@@ -27,6 +27,7 @@ To enable all of this, the integration code is accomplished by writing a handful
 ```python
 from sparseml.pytorch.optim import ScheduledModifierManager
 
+## fill in definitions below
 model = Model()  # model definition
 optimizer = Optimizer()  # optimizer definition
 train_data = TrainData()  # train data definition
@@ -58,6 +59,7 @@ To enable all of this, the integration code you'll need to write is only a handf
 ```python
 from sparseml.keras.optim import ScheduledModifierManager
 
+## fill in definitions below
 model = None  # your model definition
 optimizer = None  # your optimizer definition
 num_train_batches = len(train_data) / batch_size  # your number of batches per training epoch
@@ -94,6 +96,7 @@ The `ScheduledModifierManager` can override the necessary callbacks in the estim
 ```python
 from sparseml.tensorflow_v1.optim import ScheduledModifierManager
 
+## fill in definitions below
 estimator = None  # your estimator definition
 num_train_batches = len(train_data) / batch_size  # your number of batches per training epoch
 
@@ -118,6 +121,7 @@ from sparseml.tensorflow_v1.utils import tf_compat
 from sparseml.tensorflow_v1.optim import ScheduledModifierManager
 
 
+## fill in definitions below
 with tf_compat.Graph().as_default() as graph:
     # Normal graph setup....
     num_train_batches = len(train_data) / batch_size  # your number of batches per training epoch