message: Clarify the input types for Functional model
diff: @@ -160,6 +160,9 @@ class Model(base_layer.Layer, version_utils.ModelVersionSelector):
  model = tf.keras.Model(inputs=inputs, outputs=outputs)
  ```
  + Note: Only dicts, lists, and tuples of input tensors are supported. Nested
  + inputs are not supported (e.g. lists of list or dicts of dict).
  +
  2 - By subclassing the `Model` class: in that case, you should define your
  layers in `__init__` and you should implement the model's forward pass
  in `call`.
  @@ -466,7 +469,7 @@ class Model(base_layer.Layer, version_utils.ModelVersionSelector):
  i.e. `model(inputs)`, which relies on the underlying `call` method.
  Args:
  - inputs: A tensor or list of tensors.
  + inputs: Input tensor, or dict/list/tuple of input tensors.
  training: Boolean or boolean scalar tensor, indicating whether to run
  the `Network` in training mode or inference mode.
  mask: A mask or list of masks. A mask can be
  