No module named 'transformers.models.ijepa.configuration_ijepa'

[sidorowicz-aleksandra]

I installed transformers in version 4.46.1 and parler-tts from the github link through. I use kaggle notebooks to run the parler-tts.

!pip install transformers==4.46.1 --q
!pip install git+https://github.com/huggingface/parler-tts.git --q

After running

from parler_tts import ParlerTTSForConditionalGeneration
device = "cuda" if torch.cuda.is_available() else "cpu"
model = ParlerTTSForConditionalGeneration.from_pretrained("parler-tts/parler-tts-mini-v1").to(device)

I receive the following error:

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py in _get_module(self, module_name)

/usr/lib/python3.10/importlib/__init__.py in import_module(name, package)
    125             level += 1
--> 126     return _bootstrap._gcd_import(name[level:], package, level)
    127 

/usr/lib/python3.10/importlib/_bootstrap.py in _gcd_import(name, package, level)

/usr/lib/python3.10/importlib/_bootstrap.py in _find_and_load(name, import_)

/usr/lib/python3.10/importlib/_bootstrap.py in _find_and_load_unlocked(name, import_)

ModuleNotFoundError: No module named 'transformers.models.ijepa.configuration_ijepa'

The above exception was the direct cause of the following exception:

RuntimeError                              Traceback (most recent call last)
<ipython-input-41-b2a5dcf73a0e> in <cell line: 5>()
      3 
      4 # Load model and tokenizer
----> 5 model = ParlerTTSForConditionalGeneration.from_pretrained("parler-tts/parler-tts-mini-v1").to(device)
      6 tokenizer = AutoTokenizer.from_pretrained("parler-tts/parler-tts-mini-v1")
      7 

/usr/local/lib/python3.10/dist-packages/parler_tts/modeling_parler_tts.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
   2486         kwargs["_fast_init"] = False
   2487 
-> 2488         return super().from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
   2489 
   2490     @classmethod

/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py in from_pretrained(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)
   4128                 missing_keys = [k for k in missing_keys if k not in missing_in_group]
   4129 
-> 4130         # Some models may have keys that are not in the state by design, removing them before needlessly warning
   4131         # the user.
   4132         if cls._keys_to_ignore_on_load_missing is not None:

/usr/local/lib/python3.10/dist-packages/parler_tts/modeling_parler_tts.py in __init__(self, config, text_encoder, audio_encoder, decoder)
   2351             from transformers.models.auto.modeling_auto import AutoModel
   2352 
-> 2353             audio_encoder = AutoModel.from_config(config.audio_encoder)
   2354 
   2355         if decoder is None:

/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py in from_config(cls, config, **kwargs)
    420             trust_remote_code, config._name_or_path, has_local_code, has_remote_code
    421         )
--> 422 
    423         if has_remote_code and trust_remote_code:
    424             class_ref = config.auto_map[cls.__name__]

/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py in keys(self)
    778             (
    779                 self._load_attr_from_module(key, self._config_mapping[key]),
--> 780                 self._load_attr_from_module(key, self._model_mapping[key]),
    781             )
    782             for key in self._model_mapping.keys()

/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py in <listcomp>(.0)
    779                 self._load_attr_from_module(key, self._config_mapping[key]),
    780                 self._load_attr_from_module(key, self._model_mapping[key]),
--> 781             )
    782             for key in self._model_mapping.keys()
    783             if key in self._config_mapping.keys()

/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py in _load_attr_from_module(self, model_type, attr)
    775 
    776     def items(self):
--> 777         mapping_items = [
    778             (
    779                 self._load_attr_from_module(key, self._config_mapping[key]),

/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py in getattribute_from_module(module, attr)
    691     if isinstance(attr, tuple):
    692         return tuple(getattribute_from_module(module, a) for a in attr)
--> 693     if hasattr(module, attr):
    694         return getattr(module, attr)
    695     # Some of the mappings have entries model_type -> object of another model type. In that case we try to grab the

/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py in __getattr__(self, name)

/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py in _get_module(self, module_name)

RuntimeError: Failed to import transformers.models.ijepa.configuration_ijepa because of the following error (look up to see its traceback):
No module named 'transformers.models.ijepa.configuration_ijepa'