message: Fix list formatting on TextVectorization.
  Paren-numbered lists are not recognized on tensorflow.org
diff: @@ -89,23 +89,25 @@ class TextVectorization(CombinerPreprocessingLayer):
  to create the vocabulary.
  The processing of each sample contains the following steps:
  - 1) standardize each sample (usually lowercasing + punctuation stripping)
  - 2) split each sample into substrings (usually words)
  - 3) recombine substrings into tokens (usually ngrams)
  - 4) index tokens (associate a unique int value with each token)
  - 5) transform each sample using this index, either into a vector of ints or
  +
  + 1. standardize each sample (usually lowercasing + punctuation stripping)
  + 2. split each sample into substrings (usually words)
  + 3. recombine substrings into tokens (usually ngrams)
  + 4. index tokens (associate a unique int value with each token)
  + 5. transform each sample using this index, either into a vector of ints or
  a dense float vector.
  Some notes on passing Callables to customize splitting and normalization for
  this layer:
  - 1) Any callable can be passed to this Layer, but if you want to serialize
  +
  + 1. Any callable can be passed to this Layer, but if you want to serialize
  this object you should only pass functions that are registered Keras
  serializables (see `tf.keras.utils.register_keras_serializable` for more
  details).
  - 2) When using a custom callable for `standardize`, the data received
  + 2. When using a custom callable for `standardize`, the data received
  by the callable will be exactly as passed to this layer. The callable
  should return a tensor of the same shape as the input.
  - 3) When using a custom callable for `split`, the data received by the
  + 3. When using a custom callable for `split`, the data received by the
  callable will have the 1st dimension squeezed out - instead of
  `[["string to split"], ["another string to split"]]`, the Callable will
  see `["string to split", "another string to split"]`. The callable should
  