Applies the runtime layerwise fp8 storage cast to a model's dense text
encoder once and saves the cast state dict with baked metadata (format
tag, base_model_id, family, scheme, component, te_class, versions) in
the layout diffusion_te_prequant.py validates. Resolves the encoder
class from the checkpoint's config.architectures so the recorded
te_class matches what the pipeline instantiates. CPU-runnable: the cast
touches storage dtypes only.
