OpenGVLab/InternVideo2_5_Chat_8B · AttributeError: 'InternVLChatConfig' object has no attribute 'llm

Hello,

When I try to load the model as in the demo, I get the following error. Any ideas? Thanks a lot!

Model loading:

model_path = 'OpenGVLab/InternVideo2_5_Chat_8B'

tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
model = AutoModel.from_pretrained(model_path, trust_remote_code=True).half().cuda().to(torch.bfloat16)

Error:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[2], line 15
     12 model_path = 'OpenGVLab/InternVideo2_5_Chat_8B'
     14 tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
---> 15 model = AutoModel.from_pretrained(model_path, trust_remote_code=True).half().cuda().to(torch.bfloat16)
     18 model = AutoModel.from_pretrained("OpenGVLab/InternVideo2_5_Chat_8B", trust_remote_code=True)  

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:547, in _BaseAutoModelClass.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    544 if kwargs.get("quantization_config", None) is not None:
    545     _ = kwargs.pop("quantization_config")
--> 547 config, kwargs = AutoConfig.from_pretrained(
    548     pretrained_model_name_or_path,
    549     return_unused_kwargs=True,
    550     code_revision=code_revision,
    551     _commit_hash=commit_hash,
    552     **hub_kwargs,
    553     **kwargs,
    554 )
    556 # if torch_dtype=auto was passed here, ensure to pass it on
    557 if kwargs_orig.get("torch_dtype", None) == "auto":

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:1187, in AutoConfig.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
   1183     config_class = get_class_from_dynamic_module(
   1184         class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs
   1185     )
   1186     config_class.register_for_auto_class()
-> 1187     return config_class.from_pretrained(pretrained_model_name_or_path, **kwargs)
   1188 elif "model_type" in config_dict:
   1189     try:

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/configuration_utils.py:587, in PretrainedConfig.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision, **kwargs)
    581     if config_dict["model_type"] != cls.model_type:
    582         logger.warning(
    583             f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
    584             f"{cls.model_type}. This is not supported for all configurations of models and can yield errors."
    585         )
--> 587 return cls.from_dict(config_dict, **kwargs)

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/configuration_utils.py:775, in PretrainedConfig.from_dict(cls, config_dict, **kwargs)
    772 for key in to_remove:
    773     kwargs.pop(key, None)
--> 775 logger.info(f"Model config {config}")
    776 if return_unused_kwargs:
    777     return config, kwargs

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/configuration_utils.py:807, in PretrainedConfig.__repr__(self)
    806 def __repr__(self):
--> 807     return f"{self.__class__.__name__} {self.to_json_string()}"

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/configuration_utils.py:919, in PretrainedConfig.to_json_string(self, use_diff)
    907 """
    908 Serializes this instance to a JSON string.
    909 
   (...)
    916     `str`: String containing all the attributes that make up this configuration instance in JSON format.
    917 """
    918 if use_diff is True:
--> 919     config_dict = self.to_diff_dict()
    920 else:
    921     config_dict = self.to_dict()

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/configuration_utils.py:827, in PretrainedConfig.to_diff_dict(self)
    824 default_config_dict = PretrainedConfig().to_dict()
    826 # get class specific config dict
--> 827 class_config_dict = self.__class__().to_dict() if not self.has_no_defaults_at_init else {}
    829 serializable_config_dict = {}
    831 # Only serialize values that differ from the default config,
    832 # except always keep the 'config' attribute.

File ~/.cache/huggingface/modules/transformers_modules/OpenGVLab/InternVideo2_5_Chat_8B/bff14a1dd7647d9e81414bb91c59fdc983104f34/configuration_internvl_chat.py:85, in InternVLChatConfig.to_dict(self)
     83 output = copy.deepcopy(self.__dict__)
     84 output['vision_config'] = self.vision_config.to_dict()
---> 85 output['llm_config'] = self.llm_config.to_dict()
     86 output['model_type'] = self.__class__.model_type
     87 output['use_backbone_lora'] = self.use_backbone_lora

File ~/my_conda_envs/myenv/lib/python3.10/site-packages/transformers/configuration_utils.py:209, in PretrainedConfig.__getattribute__(self, key)
    207 if key != "attribute_map" and key in super().__getattribute__("attribute_map"):
    208     key = super().__getattribute__("attribute_map")[key]
--> 209 return super().__getattribute__(key)

AttributeError: 'InternVLChatConfig' object has no attribute 'llm_config'