[Python] error : Only instances of `keras.Layer` can be added to a Sequential model

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 ~\Desktop\TFproj\tfvenv\Lib\site-packages\keras\src\models\sequential.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 ~\Desktop\TFproj\tfvenv\Lib\site-packages\keras\src\models\sequential.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'>)

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