Exceptions for package
transformers
github stars 50617

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views 3009
text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples). / transformers
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word_ids() is not available when using Python-based tokenizers / transformers
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Some specified arguments are not used by the HfArgumentParser: (remaining_args) / transformers
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got_ver is None / transformers
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char_to_token() is not available when using Python based tokenizers / transformers
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Both extra_ids ((extra_ids)) and additional_special_tokens ((additional_special_tokens)) are provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids tokens / transformers
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views 2227
Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. / transformers
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return_offset_mapping is not available when using Python tokenizers.To use this feature, change your tokenizer to one deriving from transformers.PreTrainedTokenizerFast. / transformers
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Can only automatically infer lengths for datasets whose items are dictionaries with an '(self.model_input_name)' key. / transformers
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Make sure `_init_weigths` is implemented for (self.__class__) / transformers
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`num_return_sequences` has to be smaller or equal to `num_beams`. / transformers
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Unable to convert output to PyTorch tensors format, PyTorch is not installed. / transformers
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