Save the model weights as a h5 file extension with model.save_weights and then reload the model with [~TFPreTrainedModel.from_pretrained]:

from transformers import TFPreTrainedModel
from tensorflow import keras
model.save_weights("some_folder/tf_model.h5")
model = TFPreTrainedModel.from_pretrained("some_folder")

Save the model with [~TFPretrainedModel.save_pretrained] and load it again with [~TFPreTrainedModel.from_pretrained]: