warnings.warn(

---

AttributeError Traceback (most recent call last)

/usr/local/lib/python3.12/dist-packages/span_marker/configuration.py in getattribute(self, key)

113 try:

--> 114 return super().getattribute(key)

115 except AttributeError as e:

13 frames

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in getattribute(self, key)

206 key = super().getattribute("attribute_map")[key]

--> 207 return super().getattribute(key)

208

AttributeError: 'SpanMarkerConfig' object has no attribute '_attn_implementation_internal'

During handling of the above exception, another exception occurred:

TypeError Traceback (most recent call last)

/tmp/ipython-input-1093887576.py in <cell line: 0>()

2

3 # Download from the 🤗 Hub

----> 4 model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-mbert-base-multinerd")

5 # Run inference

6 entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")

/usr/local/lib/python3.12/dist-packages/span_marker/modeling.py in from_pretrained(cls, pretrained_model_name_or_path, labels, config, model_card_data, *model_args, **kwargs)

252 # If loading a SpanMarkerConfig, then we don't want to override id2label and label2id

253 # Create an encoder or SpanMarker config

--> 254 config: PretrainedConfig = config or AutoConfig.from_pretrained(

255 pretrained_model_name_or_path, *model_args, **kwargs

256 )

/usr/local/lib/python3.12/dist-packages/transformers/models/auto/configuration_auto.py in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)

1319 "pip install git+https://github.com/huggingface/transformers.git"

1320 )

-> 1321 return config_class.from_dict(config_dict, **unused_kwargs)

1322 else:

1323 # Fallback: use pattern matching on the string.

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in from_dict(cls, config_dict, **kwargs)

806 config_dict["attn_implementation"] = kwargs.pop("attn_implementation", None)

807

--> 808 config = cls(**config_dict)

809

810 if hasattr(config, "pruned_heads"):

/usr/local/lib/python3.12/dist-packages/span_marker/configuration.py in init(self, encoder_config, model_max_length, marker_max_length, entity_max_length, max_prev_context, max_next_context, **kwargs)

64 self.trained_with_document_context = False

65 self.span_marker_version = kwargs.pop("span_marker_version", None)

---> 66 super().init(**kwargs)

67

68 if not self.encoder:

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in init(self, output_hidden_states, output_attentions, return_dict, torchscript, dtype, pruned_heads, tie_word_embeddings, chunk_size_feed_forward, is_encoder_decoder, is_decoder, cross_attention_hidden_size, add_cross_attention, tie_encoder_decoder, architectures, finetuning_task, id2label, label2id, num_labels, task_specific_params, problem_type, tokenizer_class, prefix, bos_token_id, pad_token_id, eos_token_id, sep_token_id, decoder_start_token_id, **kwargs)

326

327 # Attention implementation to use, if relevant (it sets it recursively on sub-configs)

--> 328 self._attn_implementation = kwargs.pop("attn_implementation", None)

329

330 # Drop the transformers version info

/usr/local/lib/python3.12/dist-packages/span_marker/configuration.py in setattr(self, name, value)

108 if name == "outside_id":

109 return

--> 110 return super().setattr(name, value)

111

112 def getattribute(self, key: str) -> Any:

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in setattr(self, key, value)

200 if key in super().getattribute("attribute_map"):

201 key = super().getattribute("attribute_map")[key]

--> 202 super().setattr(key, value)

203

204 def getattribute(self, key):

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in _attn_implementation(self, value)

412 """We set it recursively on the sub-configs as well"""

413 # Set if for current config

--> 414 current_attn = getattr(self, "_attn_implementation", None)

415 attn_implementation = value if not isinstance(value, dict) else value.get("", current_attn)

416 self._attn_implementation_internal = attn_implementation

/usr/local/lib/python3.12/dist-packages/span_marker/configuration.py in getattribute(self, key)

112 def getattribute(self, key: str) -> Any:

113 try:

--> 114 return super().getattribute(key)

115 except AttributeError as e:

116 try:

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in getattribute(self, key)

205 if key != "attribute_map" and key in super().getattribute("attribute_map"):

206 key = super().getattribute("attribute_map")[key]

--> 207 return super().getattribute(key)

208

209 def init(

/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py in _attn_implementation(self)

406 @property

407 def _attn_implementation(self):

--> 408 return self._attn_implementation_internal

409

410 @_attn_implementation.setter

/usr/local/lib/python3.12/dist-packages/span_marker/configuration.py in getattribute(self, key)

115 except AttributeError as e:

116 try:

--> 117 return super().getattribute("encoder")[key]

118 except KeyError:

119 raise e

TypeError: 'NoneType' object is not subscriptable

from span_marker import SpanMarkerModel

Download from the 🤗 Hub

model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-mbert-base-multinerd")

Run inference

entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")