kermt-add-cmim-pretrain

Convert a grover_base checkpoint (legacy original-GROVER grover.encoders.* or modern kermt.encoders.*, with or without vocab heads) into a fully-formed hybrid (cMIM + vocab) checkpoint, then continue pretraining on the user's corpus as hybrid.

This is a thin wrapper: upgrade_to_hybrid.py produces a new ckpt that classifies as model_type: hybrid via check_checkpoint.py, and the rest of the workflow is identical to kermt-continue-pretrain.

Status: experimental. This workflow is functional end-to-end but has not been benchmarked against the manuscript's from-scratch hybrid training (which produces the released checkpoint). Use as an experimental alternative to kermt-pretrain-scratch when you want to extend an existing grover_base checkpoint rather than restart from random init. Validate downstream performance on your own benchmark before relying on the upgraded ckpt for production work.