def _load_pretrained_tok2vec(nlp, loc):
    """Load pretrained weights for the 'token-to-vector' part of the component
    models, which is typically a CNN. See 'spacy pretrain'. Experimental.
    """
    with loc.open('rb') as file_:
        weights_data = file_.read()
    loaded = []
    for name, component in nlp.pipeline:
        if hasattr(component, 'model') and hasattr(component.model, 'tok2vec'):
            component.tok2vec.from_bytes(weights_data)
            loaded.append(name)
    return loaded
