def freeze_embeds(model):
    """Freeze token embeddings and positional embeddings for bart, just token embeddings for t5."""
    model_type = model.config.model_type

    if model_type == "t5":
        freeze_params(model.shared)
        for d in [model.encoder, model.decoder]:
            freeze_params(d.embed_tokens)
    elif model_type == "fsmt":
        for d in [model.model.encoder, model.model.decoder]:
            freeze_params(d.embed_positions)
            freeze_params(d.embed_tokens)
    else:
        freeze_params(model.model.shared)
        for d in [model.model.encoder, model.model.decoder]:
            freeze_params(d.embed_positions)
            freeze_params(d.embed_tokens)
Freeze token embeddings and positional embeddings for bart, just token embeddings for t5.
dpkd/transformers/examples/research_projects/seq2seq-distillation/utils.py