Error on google colab and kaggle
KeyError Traceback (most recent call last)
/usr/local/lib/python3.11/dist-packages/transformers/models/auto/configuration_auto.py in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
1270 try:
-> 1271 config_class = CONFIG_MAPPING[config_dict["model_type"]]
1272 except KeyError:
/usr/local/lib/python3.11/dist-packages/transformers/models/auto/configuration_auto.py in getitem(self, key)
965 if key not in self._mapping:
--> 966 raise KeyError(key)
967 value = self._mapping[key]
KeyError: 'llava_llama'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
/tmp/ipykernel_36/3840597437.py in <cell line: 0>()
2 from transformers import pipeline
3
----> 4 pipe = pipeline("image-text-to-text", model="LANSG/GEM")
/usr/local/lib/python3.11/dist-packages/transformers/pipelines/init.py in pipeline(task, model, config, tokenizer, feature_extractor, image_processor, processor, framework, revision, use_fast, token, device, device_map, torch_dtype, trust_remote_code, model_kwargs, pipeline_class, **kwargs)
907 model = adapter_config["base_model_name_or_path"]
908
--> 909 config = AutoConfig.from_pretrained(
910 model, _from_pipeline=task, code_revision=code_revision, **hub_kwargs, **model_kwargs
911 )
/usr/local/lib/python3.11/dist-packages/transformers/models/auto/configuration_auto.py in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
1271 config_class = CONFIG_MAPPING[config_dict["model_type"]]
1272 except KeyError:
-> 1273 raise ValueError(
1274 f"The checkpoint you are trying to load has model type {config_dict['model_type']} "
1275 "but Transformers does not recognize this architecture. This could be because of an "
ValueError: The checkpoint you are trying to load has model type llava_llama but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.
You can update Transformers with the command pip install --upgrade transformers. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command pip install git+https://github.com/huggingface/transformers.git