Using LaBSE deployed to Google Cloud AI Platform - tensorflow

Question

I deployed LaBSE model to AI Platform in the last past few days.
The issue I encounter is the answer of the request is above the limit of 2MB.
Several ideas I had to improve the situation:
make AI Platform return minified (not beautifully formatted) JSON (without spaces and newlines everywhere
make AI Plateform return the results in a binary format
since the answer is composed of ~13 outputs : change it to only one output
Do you know any ways of doing 1) or 2) ?
I spent lost of efforts on 3). I'm sure this one is possible. For example by editing the network before uploading it. Here are stuff I tried so far for that:
VERSION = 'v1'
MODEL = 'labse_2_b'
MODEL_DIR = BUCKET + '/' + MODEL
# Download the model
! wget 'https://tfhub.dev/google/LaBSE/2?tf-hub-format=compressed' \
--output-document='{MODEL}.tar.gz'
! mkdir {MODEL}
! tar -xzvf '{MODEL}.tar.gz' -C {MODEL}
# Attempts to load the model, edit it, and save it:
model.save(export_path, save_format='tf') # ValueError: Model <keras.engine.sequential.Sequential object at 0x7f87e833c650>
# cannot be saved because the input shapes have not been set.
# Usually, input shapes are automatically determined from calling
# `.fit()` or `.predict()`.
# To manually set the shapes, call `model.build(input_shape)`.
model.build(input_shape=(None,)) # cannot find a proper shape
# create a AI Plateform model version:
! gsutil -m cp -r '{MODEL}' {MODEL_DIR} # upload model to Google Cloud Storage
! gcloud ai-platform versions create $VERSION \
--model {MODEL} \
--origin {MODEL_DIR} \
--runtime-version=2.1 \
--framework='tensorflow' \
--python-version=3.7 \
--region="{REGION}"
Could some please help with with that?
Thanks a lot in advance,
EDIT :
For those wondering about this limitation, as in the comments below : Here are some complementary pieces of information:
A short sentence as
"I wish you a pleasant flight and a good meal aboard this plane."
which is just 16 parts of words long:
[101, 146, 34450, 15100, 170, 147508, 48088, 14999, 170, 17072, 66369, 351617, 15272, 69746, 119, 102]
cannot be processed:
Response size too large. Received at least 3220082 bytes; max is 2000000.". Details: "Response size too large. Received at least 3220082 bytes; max is 2000000.