Python gpt-2-simple, load multiple models at once

I'm working on a discord bot and one of the functions I want to implement responds with text generated by the gpt-2-simple library. I want to have more then one model loaded to have multiple models available to respond to messages from my users.

However I get the following error when i run the load_gpt2() function in the second model

File "main.py", line 22, in <module>
    main()
  File "main.py", line 16, in main
    text_events.register_Message(client)
  File "U:\discord_bot\text_events\__init__.py", line 19, in register_Message
    event.init()
  File "U:\discord_bot\text_events\model2.py", line 20, in init
    gpt2.load_gpt2(sess, run_name='model2', checkpoint_dir="characters")
  File "C:\Program Files\Python36\lib\site-packages\gpt_2_simple\gpt_2.py", line 389, in load_gpt2
    output = model.model(hparams=hparams, X=context, gpus=gpus)
  File "C:\Program Files\Python36\lib\site-packages\gpt_2_simple\src\model.py", line 183, in model
    initializer=tf.compat.v1.random_normal_initializer(stddev=0.01))
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\ops\variable_scope.py", line 1500, in get_variable
    aggregation=aggregation)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\ops\variable_scope.py", line 1243, in get_variable
    aggregation=aggregation)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\ops\variable_scope.py", line 567, in get_variable
    aggregation=aggregation)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\ops\variable_scope.py", line 519, in _true_getter
    aggregation=aggregation)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\ops\variable_scope.py", line 868, in _get_single_variable
    (err_msg, "".join(traceback.format_list(tb))))
ValueError: Variable model/wpe already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:

  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "C:\Program Files\Python36\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)

I've tried to find a way to keep the gpt2 instances seperate between modules but i can't find anything that achieves this sandboxing effect, or any other advice for seperating the models or their instances. Does anyone have any ideas?

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