IDEA-Research

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grounding-dino-base

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KeyError: 'grounding-dino' encountered when running the inference example. It appears 'grounding-dino' is missing from CONFIG_MAPPING for the AutoModelForZeroShotObjectDetection class which propagates a ValueError. For reference I'm running the latest version of transformers (4.39.3) with python 3.10.

Full Traceback below:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File ./python3.10/site-packages/transformers/models/auto/configuration_auto.py:1155, in AutoConfig.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
   1154 try:
-> 1155     config_class = CONFIG_MAPPING[config_dict["model_type"]]
   1156 except KeyError:

File ./python3.10/site-packages/transformers/models/auto/configuration_auto.py:852, in _LazyConfigMapping.__getitem__(self, key)
    851 if key not in self._mapping:
--> 852     raise KeyError(key)
    853 value = self._mapping[key]

KeyError: 'grounding-dino'

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
Cell In[3], line 11
      8 device = 'mps'
     10 processor = AutoProcessor.from_pretrained(model_id)
---> 11 model = AutoModelForZeroShotObjectDetection.from_pretrained(model_id).to(device)
     13 image_url = "http://images.cocodataset.org/val2017/000000039769.jpg"
     14 image = Image.open(requests.get(image_url, stream=True).raw)

File ./python3.10/site-packages/transformers/models/auto/auto_factory.py:523, in _BaseAutoModelClass.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    520 if kwargs.get("quantization_config", None) is not None:
    521     _ = kwargs.pop("quantization_config")
--> 523 config, kwargs = AutoConfig.from_pretrained(
    524     pretrained_model_name_or_path,
    525     return_unused_kwargs=True,
    526     trust_remote_code=trust_remote_code,
    527     code_revision=code_revision,
    528     _commit_hash=commit_hash,
    529     **hub_kwargs,
    530     **kwargs,
    531 )
    533 # if torch_dtype=auto was passed here, ensure to pass it on
    534 if kwargs_orig.get("torch_dtype", None) == "auto":

File ./python3.10/site-packages/transformers/models/auto/configuration_auto.py:1157, in AutoConfig.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
   1155         config_class = CONFIG_MAPPING[config_dict["model_type"]]
   1156     except KeyError:
-> 1157         raise ValueError(
   1158             f"The checkpoint you are trying to load has model type `{config_dict['model_type']}` "
   1159             "but Transformers does not recognize this architecture. This could be because of an "
   1160             "issue with the checkpoint, or because your version of Transformers is out of date."
   1161         )
   1162     return config_class.from_dict(config_dict, **unused_kwargs)
   1163 else:
   1164     # Fallback: use pattern matching on the string.
   1165     # We go from longer names to shorter names to catch roberta before bert (for instance)

ValueError: The checkpoint you are trying to load has model type `grounding-dino` 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.