How to save a Lightning model that contains a PyTorch model with customized saving function
❓ Questions and Help
What is your question?
I'd like to use Lightning to do the training of a PyTorch transformer model. So I wrap the transformer model in a LightningModule. Before training, the model is initialized from a pre-trained model by use of hparams. I use default saving with Lightning. However, the transformer itself has a very specific save/load method. Ideally we would like the transformer model to save using its own method instead of relying on Lightning. My questions are:

How do I save the Lightning model correctly so that it uses the specific save/load method for the wrapped transformer model?
How do I load the saved checkpoint correctly so that it will not load the pre-trained model indicated by hparams?

Code
import transformers
class Transformer(LightningModule):
  def __init__(self, hparams):
    ...

    # Initialize the pytorch model (dependent on an external pre-trained model)
    self.transformer = transformers.from_pretrained(params.transformer_name)

    # note: self.transformer has a method save_pretrained to save it in a directory so ideally we would like it to be saved with its own method instead of default one provided by Lightning

model = Transformer(hparams)
trainer = Trainer(..)
trainer.fit(model)

What have you tried?
I tried the default saving with Lightning but not sure if this is correct.
What's your environment?

OS: Linux
Packaging pip
Version 0.9.0