dictionnary => dictionary
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@@ -37,7 +37,7 @@ class PreTrainedTokenizer(object):
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additional_special_tokens = []
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We defined an added_tokens_encoder to add new tokens to the vocabulary without having to handle the
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specific vocabulary augmentation methods of the various underlying dictionnary structures (BPE, sentencepiece...).
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specific vocabulary augmentation methods of the various underlying dictionary structures (BPE, sentencepiece...).
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"""
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vocab_files_names = {}
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pretrained_vocab_files_map = {}
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@@ -324,7 +324,7 @@ class PreTrainedTokenizer(object):
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def add_special_tokens(self, special_tokens_dict):
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""" Add a dictionnary of special tokens (eos, pad, cls...) to the encoder and link them
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""" Add a dictionary of special tokens (eos, pad, cls...) to the encoder and link them
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to class attributes. If the special tokens are not in the vocabulary, they are added
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to it and indexed starting from the last index of the current vocabulary.
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