i simply want to wrap the model as a keras layer but it simply is not happening ans keeps showing this error to me, i don’t know if it’s the keras or tensorflow version but i don’t want to change them so is there an alternative ?
this is the code i used

mobilenet_v2 ="https://tfhub.dev/google/tf2-preview/mobilenet_v2/classification/4"

classifier_model = mobilenet_v2

IMAGE_SHAPE = (224, 224)

classifier = tf.keras.Sequential([
    hub.KerasLayer(classifier_model, input_shape=IMAGE_SHAPE+(3,))
])

and this is the complete error :

ValueError                                Traceback (most recent call last)
Cell In[8], line 3
      1 IMAGE_SHAPE = (224, 224)
----> 3 classifier = tf.keras.Sequential([
      4     hub.KerasLayer(classifier_model, input_shape=IMAGE_SHAPE+(3,))
      5 ])

File ~DesktopTFprojtfvenvLibsite-packageskerassrcmodelssequential.py:73, in Sequential.__init__(self, layers, trainable, name)
     71 if layers:
     72     for layer in layers:
---> 73         self.add(layer, rebuild=False)
     74     self._maybe_rebuild()

File ~DesktopTFprojtfvenvLibsite-packageskerassrcmodelssequential.py:95, in Sequential.add(self, layer, rebuild)
     93         layer = origin_layer
     94 if not isinstance(layer, Layer):
---> 95     raise ValueError(
     96         "Only instances of `keras.Layer` can be "
     97         f"added to a Sequential model. Received: {layer} "
     98         f"(of type {type(layer)})"
     99     )
    100 if not self._is_layer_name_unique(layer):
    101     raise ValueError(
    102         "All layers added to a Sequential model "
    103         f"should have unique names. Name '{layer.name}' is already "
    104         "the name of a layer in this model. Update the `name` argument "
    105         "to pass a unique name."
    106     )

ValueError: Only instances of `keras.Layer` can be added to a Sequential model. Received: <tensorflow_hub.keras_layer.KerasLayer object at 0x0000021DD8434FB0> (of type <class 'tensorflow_hub.keras_layer.KerasLayer'>)