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]

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")
`

[arrshsh]

Same issue, please do let me know if you find some solution around this issue

[masrik-dev]

Could you let me know if you found the solution?

[naman22a]

use tf-keras
pip install tf-keras
import tf_keras as keras
replace tf.keras with keras