TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

[SEUNKOREA]

아래의 링크에 있는 코드에서
https://github.com/tabtoyou/KoLLaVA/blob/main/KoLLaVA-v1-Kovicuna-7b_inference.ipynb]

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import os
from llava.conversation import conv_templates, SeparatorStyle
from llava.utils import disable_torch_init
from transformers import CLIPVisionModel, CLIPImageProcessor, StoppingCriteria
from llava.model import *
from llava.model.utils import KeywordsStoppingCriteria

실행하면 다음과 같은 오류가 발생합니다.

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[11], line 4
      2 import torch
      3 import os
----> 4 from llava.conversation import conv_templates, SeparatorStyle
      5 from llava.utils import disable_torch_init
      6 from transformers import CLIPVisionModel, CLIPImageProcessor, StoppingCriteria

File /home/share/LSE/hde-intg/KoLLaVA/llava/__init__.py:1
----> 1 from .model import LlavaLlamaForCausalLM

File /home/share/LSE/hde-intg/KoLLaVA/llava/model/__init__.py:1
----> 1 from .language_model.llava_llama import LlavaLlamaForCausalLM, LlavaConfig
      2 from .language_model.llava_mpt import LlavaMPTForCausalLM, LlavaMPTConfig

File /home/share/LSE/hde-intg/KoLLaVA/llava/model/language_model/llava_llama.py:40
     36     def __init__(self, config: LlamaConfig):
     37         super(LlavaLlamaModel, self).__init__(config)
---> 40 class LlavaLlamaForCausalLM(LlamaForCausalLM, LlavaMetaForCausalLM):
     41     config_class = LlavaConfig
     43     def __init__(self, config):

TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

[SEUNKOREA]

커널 재시작 후에 위의 에러는 사라졌는데 아래와 같은 에러가 발생했습니다.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[3], line 4
      2 import torch
      3 import os
----> 4 from llava.conversation import conv_templates, SeparatorStyle
      5 from llava.utils import disable_torch_init
      6 from transformers import CLIPVisionModel, CLIPImageProcessor, StoppingCriteria

File /home/share/LSE/hde-intg/KoLLaVA/llava/__init__.py:1
----> 1 from .model import LlavaLlamaForCausalLM

File /home/share/LSE/hde-intg/KoLLaVA/llava/model/__init__.py:1
----> 1 from .language_model.llava_llama import LlavaLlamaForCausalLM, LlavaConfig
      2 from .language_model.llava_mpt import LlavaMPTForCausalLM, LlavaMPTConfig

File /home/share/LSE/hde-intg/KoLLaVA/llava/model/language_model/llava_llama.py:110
    107             _inputs['images'] = images
    108         return _inputs
--> 110 AutoConfig.register("llava", LlavaConfig)
    111 AutoModelForCausalLM.register(LlavaConfig, LlavaLlamaForCausalLM)

File ~/envs/hde-intg-dev-3.10/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:1074, in AutoConfig.register(model_type, config, exist_ok)
   1068 if issubclass(config, PretrainedConfig) and config.model_type != model_type:
   1069     raise ValueError(
   1070         "The config you are passing has a `model_type` attribute that is not consistent with the model type "
   1071         f"you passed (config has {config.model_type} and you passed {model_type}. Fix one of those so they "
   1072         "match!"
   1073     )
-> 1074 CONFIG_MAPPING.register(model_type, config, exist_ok=exist_ok)

File ~/envs/hde-intg-dev-3.10/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:773, in _LazyConfigMapping.register(self, key, value, exist_ok)
    769 """
    770 Register a new configuration in this mapping.
    771 """
    772 if key in self._mapping.keys() and not exist_ok:
--> 773     raise ValueError(f"'{key}' is already used by a Transformers config, pick another name.")
    774 self._extra_content[key] = value

ValueError: 'llava' is already used by a Transformers config, pick another name.