def _get_model_loader(model_name: str, model_properties: dict) -> Any:
    """ Returns a dict describing properties of a model.

    These properties will be used by the tensor_search application to set up
    index parameters.

    see https://huggingface.co/sentence-transformers for available models

    TODO: standardise these dicts

    Returns:
        dict: a dictionary describing properties of the model.
    """

    model_type = model_properties['type']

    if model_type not in MODEL_PROPERTIES['loaders']:
        raise KeyError(f"model_name={model_name} for model_type={model_type} not in allowed model types")

    return MODEL_PROPERTIES['loaders'][model_type]
 Returns a dict describing properties of a model.

    These properties will be used by the tensor_search application to set up
    index parameters.

    see https://huggingface.co/sentence-transformers for available models

    TODO: standardise these dicts

    Returns:
        dict: a dictionary describing properties of the model.
    
src/marqo/inference/native_inference/load_model.py