Model cannot be save - universal-sentence-encoder-qa - tensorflow

Question

I have spent few hours to troubleshoot this issue but not clue.... hope someone can help.
The error I got it below
ValueError: Model XXXXXXX cannot be saved either because the input shape is not available or because the forward pass of the model is not defined.To define a forward pass, please override Model.call(). To specify an input shape, either call build(input_shape) directly, or call the model on actual data using Model(), Model.fit(), or Model.predict(). If you have a custom training step, please make sure to invoke the forward pass in train step through Model.call_, i.e. model(inputs), as opposed to model.call().
import tensorflow as tf
import tensorflow_hub as hub
class queryEncoder(tf.keras.Model):
def __init__(self):
super().__init__()
module = hub.load('https://tfhub.dev/google/universal-sentence-encoder-qa/3')
self.encoder = module.signatures['question_encoder']
def call(self, inputs):
return self.encoder(input=tf.constant(inputs))['outputs']
qModel = queryEncoder()
qModel.save('use-query-encoder')
!gsutil cp use-query-encoder gs://ed-model-artifacts-xxyyzz
Actually, what I wanted to do is follow Google's youtube to build a Q&A model with Vertex AI.
https://www.youtube.com/watch?v=5iSmX8sqtx8
But the tutorial didn't give any source code, so I typed the codes follow the video.
If I didn't run qModel.save('use-query-encoder') , but run qModel((["This is hello world"])) , it seems works - returning embedding successfully.
So, the model should be working fine, but some how cannot be save.
I read a lot of posts in Stackoverflow, but I still cannot solve my issue. Perhaps I am too new to Python and TF. I found some posts said, I should run fit() before save(). However, in this can I don't know what parameters should be put in fit()...
I am newbie to Python, perhaps I did some silly thing. If so, please point out :)