Oh sorry, from the docstring, this will work:
` :param bool continue_last_task: Continue the execution of a previously executed Task (experiment)

.. note::
    When continuing the executing of a previously executed Task,
    all previous artifacts / models/ logs are intact.
    New logs will continue iteration/step based on the previous-execution maximum iteration value.
    For example:
    The last train/loss scalar reported was iteration 100, the next report will be iteration 101.

The values are:

- ``True`` - Continue the last Task ID.
    specified explicitly by reuse_last_task_id or implicitly with the same logic as reuse_last_task_id
- ``False`` - Overwrite the execution of previous Task  (default).
- A string - You can also specify a Task ID (string) to be continued.
    This is equivalent to `continue_last_task=True` and `reuse_last_task_id=a_task_id_string`.
- An integer - Specify initial iteration offset (override the auto automatic last_iteration_offset)
    Pass 0, to disable the automatic last_iteration_offset or specify a different initial offset
    You can specify a Task ID to be used with `reuse_last_task_id='task_id_here'` `

Notice we are actually setting the last iteration manually at initialization time, should do the trick
task = Task.init(project_name='OCR/CRNN', task_type='training', task_name='CRNN from scratch', reuse_last_task_id=True, continue_last_task=int(0))