The model does not save and load correctly when containing `tf.keras.layers.experimental.preprocessing.StringLookup` layer
@oawxkw,
I was able to reproduce the issue on tensorflow [v2.12](https://colab.research.google.com/gist/tilakrayal/58f9ce1b1f256c865ecf4beca79723a5/untitled1353.ipynb), [v2.13](https://colab.research.google.com/gist/tilakrayal/07ab41ec574cb435e1a47f40fe5c8892/untitled1353.ipynb) and tf-nightly. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/28dc3a29ada082719722aee96bfc5fe1/untitled1354.ipynb).

Thank you for opening this issue. Development of keras moved to another [repository](https://github.com/keras-team/keras/issues). 

Could you please post this issue on keras-team/keras [repo](https://github.com/keras-team/keras/issues).
To know more please refer:
https://discuss.tensorflow.org/t/keras-project-moved-to-new-repository-in-https-github-com-keras-team-keras/1999
Thank you!

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### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

binary

### TensorFlow version

2.14.0-rc1

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

The model does not save and load correctly when containing `tf.keras.layers.experimental.preprocessing.StringLookup` layer.
It seems that the `vocabulary` is not saved or loaded correctly, which is empty when loading the model.
This behavior may relate to #61369, but different API endpoint.


### Standalone code to reproduce the issue

```python
import pickle
import tensorflow as tf
print(tf.version.GIT_VERSION, tf.version.VERSION, flush=True)

model_input = tf.keras.Input(shape=(1,), dtype=tf.int64)
lookup = tf.keras.layers.experimental.preprocessing.StringLookup(vocabulary=['a', 'b'])(model_input)
output = tf.keras.layers.Dense(10)(lookup)
full_model = tf.keras.Model(model_input, output)

# this part works
try:
    model_bytes = pickle.dumps(full_model)
    model_recovered = pickle.loads(model_bytes)
except Exception as e:
    print("Failed! Error:", e, flush=True)
else:
    print("Success!", flush=True)

# this part throws an error
try:
    full_model.save("/tmp/temp_model")
    full_model_loaded = tf.keras.models.load_model("/tmp/temp_model")
    model_bytes = pickle.dumps(full_model_loaded)
    model_recovered = pickle.loads(model_bytes)
except Exception as e:
    print("Failed! Error:", e, flush=True)
else:
    print("Success!", flush=True)
```


### Relevant log output

```text
v2.14.0-rc0-34-gdd01672d9a9 2.14.0-rc1
Success!
WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.
WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.
Failed! Error: Error when deserializing class 'StringLookup' using config={'name': 'string_lookup', 'trainable': True, 'dtype': 'int64', 'invert': False, 'max_tokens': None, 'num_oov_indices': 1, 'oov_token': '[UNK]', 'mask_token': None, 'output_mode': 'int', 'sparse': False, 'pad_to_max_tokens': False, 'idf_weights': None, 'vocabulary': [], 'vocabulary_size': 3, 'encoding': 'utf-8'}.

Exception encountered: Cannot set an empty vocabulary, you passed [].
```
