ValueError: Only instances of keras.Layer can be added to a Sequential model. Received: <tensorflow_hub.keras_layer.KerasLayer object at 0x7a9a39daf130> (of type <class 'tensorflow_hub.keras_layer.KerasLayer'>)

[moatednorth]

Discussed in #662

^{Originally posted by moatednorth July 31, 2024}
Sequential api can't handle hub.KerasLayer

`

Create a Keras Layer using the USE pretrained layer from Kaggle

sentence_encoder_layer = hub.KerasLayer("https://www.kaggle.com/models/google/universal-sentence-encoder/TensorFlow2/universal-sentence-encoder/2",
input_shape=[],
dtype=tf.string,
trainable=False,
name="USE")

Create model using the Sequential API

model_6 = tf.keras.Sequential([
sentence_encoder_layer,
layers.Dense(64, activation="relu"),
layers.Dense(1, activation="sigmoid", name="ouput_layer")
], name="model_6_USE")
`

[AnilKamath27]

Hi, moatednorth. This is an issue that is occurring in the latest version of tensorflow 2.17. This won't be an issue if you try with tf 2.15.0. Below is a screenshot of my notebook where I was able to use hub.KerasLayers as part of Sequential API.