Since there is this paper MiniLLM I do not see any problem of having an general framework for Knowledge Distillation. The only limitation is that 2 models should share the same Tokenizer, and maybe booth have to have the same CausalLM Denoising objective, but I thing it would be enough that they predict token by token.
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