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When running the example mentioned in readme file In colab I encountered the following error
from dataclasses import dataclass
from pytorch_ie.annotations import LabeledSpan
from pytorch_ie.auto import AutoPipeline
from pytorch_ie.core import AnnotationLayer, annotation_field
from pytorch_ie.documents import TextDocument
@dataclass
class ExampleDocument(TextDocument):
entities: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
document = ExampleDocument(
"“Making a super tasty alt-chicken wing is only half of it,” said Po Bronson, general partner at SOSV and managing director of IndieBio."
)
# see below for the long version
ner_pipeline = AutoPipeline.from_pretrained("pie/example-ner-spanclf-conll03", device=-1, num_workers=0)
ner_pipeline(document)
for entity in document.entities.predictions:
print(f"{entity} -> {entity.label}")
---------------------------------------------------------------------------
RegistrationError Traceback (most recent call last)
[<ipython-input-6-266b4f95f95f>](https://localhost:8080/#) in <cell line: 19>()
17
18 # see below for the long version
---> 19 ner_pipeline = AutoPipeline.from_pretrained("pie/example-ner-spanclf-conll03", device=-1, num_workers=0)
20
21 ner_pipeline(document)
4 frames
[/usr/local/lib/python3.10/dist-packages/pytorch_ie/auto.py](https://localhost:8080/#) in from_pretrained(pretrained_model_name_or_path, force_download, resume_download, proxies, use_auth_token, cache_dir, local_files_only, taskmodule_kwargs, model_kwargs, device, binary_output, **kwargs)
126 model_kwargs = model_kwargs or {}
127
--> 128 taskmodule = AutoTaskModule.from_pretrained(
129 pretrained_model_name_or_path=pretrained_model_name_or_path,
130 force_download=force_download,
[/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py](https://localhost:8080/#) in _inner_fn(*args, **kwargs)
116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
117
--> 118 return fn(*args, **kwargs)
119
120 return _inner_fn # type: ignore
[/usr/local/lib/python3.10/dist-packages/pytorch_ie/core/hf_hub_mixin.py](https://localhost:8080/#) in from_pretrained(cls, pretrained_model_name_or_path, force_download, resume_download, proxies, token, cache_dir, local_files_only, revision, **model_kwargs)
182 model_kwargs["is_from_pretrained"] = True
183
--> 184 return cls._from_pretrained(
185 model_id=str(model_id),
186 revision=revision,
[/usr/local/lib/python3.10/dist-packages/pytorch_ie/auto.py](https://localhost:8080/#) in _from_pretrained(cls, model_id, revision, cache_dir, force_download, proxies, resume_download, local_files_only, token, map_location, strict, config, **taskmodule_kwargs)
93 config.update(taskmodule_kwargs)
94 class_name = config.pop(cls.config_type_key)
---> 95 clazz: Type[TaskModule] = TaskModule.by_name(class_name)
96 taskmodule = clazz(**config)
97 taskmodule.post_prepare()
[/usr/local/lib/python3.10/dist-packages/pytorch_ie/core/registrable.py](https://localhost:8080/#) in by_name(cls, name)
46 return Registrable._registry[cls][name]
47
---> 48 raise RegistrationError(f"{name} is not a registered name for {cls.__name__}.")
49
50 @classmethod
RegistrationError: TransformerSpanClassificationTaskModule is not a registered name for TaskModule.
The text was updated successfully, but these errors were encountered:
When running the example mentioned in readme file In colab I encountered the following error
The text was updated successfully, but these errors were encountered: