def METHOD_NAME(model: NNCFNetwork, transformations: List[PTInsertionCommand]) -> NNCFNetwork:
    """
    Applies insertion transformations to the model.
    :param model: Model to apply transformations.
    :param transformations: List of the bias correction transformations.
    """
    node_to_op_address_mapping = model.nncf.get_node_to_op_address_mapping()
    fns_grouped_by_points = {}  # type: Dict[PTInsertionPoint, List[Tuple[Callable, TransformationPriority]]]
    for transformation_command in transformations:  # type: PTInsertionCommand
        target_point = transformation_command.target_point  # type: PTTargetPoint
        target_node_name = target_point.target_node_name
        pt_ip = PTInsertionPoint(
            target_type=target_point.target_type,
            op_address=node_to_op_address_mapping[target_node_name],
            input_port_id=target_point.input_port_id,
        )
        fn = transformation_command.fn
        if target_point.type is TargetType.OPERATION_WITH_WEIGHTS:
            fn = UpdateWeight(fn)
        tup = (fn, transformation_command.priority)
        if pt_ip not in fns_grouped_by_points:
            fns_grouped_by_points[pt_ip] = [tup]
        else:
            fns_grouped_by_points[pt_ip].append(tup)
    for pt_ip, fn_list_with_priority in fns_grouped_by_points.items():
        fn_list_with_priority = sorted(fn_list_with_priority, key=lambda x: x[1])
        model.nncf.insert_at_point(pt_ip, [x[0] for x in fn_list_with_priority])
    return model