We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Hi Im using transformers version '4.26.1' on databricks. The code below return the following error
Code:
model_path = "cardiffnlp/twitter-xlm-roberta-base-sentiment" sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
Error:
AttributeError: module 'google.protobuf.descriptor' has no attribute '_internal_create_key' --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <command-798773577171854> in <module> 15 16 model_path = "cardiffnlp/twitter-xlm-roberta-base-sentiment" ---> 17 sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path) 18 19 df_group_notna['sentiment'] = df_group_notna['Feedback'].apply(lambda x: sentiment_task(x)[0]['label']) /databricks/python/lib/python3.7/site-packages/transformers/pipelines/__init__.py in pipeline(task, model, config, tokenizer, feature_extractor, framework, revision, use_fast, use_auth_token, device, device_map, torch_dtype, trust_remote_code, model_kwargs, pipeline_class, **kwargs) 827 828 tokenizer = AutoTokenizer.from_pretrained( --> 829 tokenizer_identifier, use_fast=use_fast, _from_pipeline=task, **hub_kwargs, **tokenizer_kwargs 830 ) 831 /databricks/python/lib/python3.7/site-packages/transformers/models/auto/tokenization_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs) 674 tokenizer_class_py, tokenizer_class_fast = TOKENIZER_MAPPING[type(config)] 675 if tokenizer_class_fast and (use_fast or tokenizer_class_py is None): --> 676 return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) 677 else: 678 if tokenizer_class_py is not None: /databricks/python/lib/python3.7/site-packages/transformers/tokenization_utils_base.py in from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs) 1811 local_files_only=local_files_only, 1812 _commit_hash=commit_hash, -> 1813 **kwargs, 1814 ) 1815 /databricks/python/lib/python3.7/site-packages/transformers/tokenization_utils_base.py in _from_pretrained(cls, resolved_vocab_files, pretrained_model_name_or_path, init_configuration, use_auth_token, cache_dir, local_files_only, _commit_hash, *init_inputs, **kwargs) 1957 # Instantiate tokenizer. 1958 try: -> 1959 tokenizer = cls(*init_inputs, **init_kwargs) 1960 except OSError: 1961 raise OSError( /databricks/python/lib/python3.7/site-packages/transformers/models/xlm_roberta/tokenization_xlm_roberta_fast.py in __init__(self, vocab_file, tokenizer_file, bos_token, eos_token, sep_token, cls_token, unk_token, pad_token, mask_token, **kwargs) 163 pad_token=pad_token, 164 mask_token=mask_token, --> 165 **kwargs, 166 ) 167 /databricks/python/lib/python3.7/site-packages/transformers/tokenization_utils_fast.py in __init__(self, *args, **kwargs) 112 elif slow_tokenizer is not None: 113 # We need to convert a slow tokenizer to build the backend --> 114 fast_tokenizer = convert_slow_tokenizer(slow_tokenizer) 115 elif self.slow_tokenizer_class is not None: 116 # We need to create and convert a slow tokenizer to build the backend /databricks/python/lib/python3.7/site-packages/transformers/convert_slow_tokenizer.py in convert_slow_tokenizer(transformer_tokenizer) 1160 converter_class = SLOW_TO_FAST_CONVERTERS[tokenizer_class_name] 1161 -> 1162 return converter_class(transformer_tokenizer).converted() /databricks/python/lib/python3.7/site-packages/transformers/convert_slow_tokenizer.py in __init__(self, *args) 436 super().__init__(*args) 437 --> 438 from .utils import sentencepiece_model_pb2 as model_pb2 439 440 m = model_pb2.ModelProto() /databricks/python/lib/python3.7/site-packages/transformers/utils/sentencepiece_model_pb2.py in <module> 32 syntax="proto2", 33 serialized_options=b"H\003", ---> 34 create_key=_descriptor._internal_create_key, 35 serialized_pb=( 36 b'\n\x19sentencepiece_model.proto\x12\rsentencepiece"\xa1\n\n\x0bTrainerSpec\x12\r\n\x05input\x18\x01' AttributeError: module 'google.protobuf.descriptor' has no attribute '_internal_create_key'
The text was updated successfully, but these errors were encountered:
No branches or pull requests
Hi
Im using transformers version '4.26.1' on databricks. The code below return the following error
Code:
Error:
The text was updated successfully, but these errors were encountered: