diff --git a/pytorch_transformers/modeling_roberta.py b/pytorch_transformers/modeling_roberta.py
index e49b2a06..cbd88ab8 100644
--- a/pytorch_transformers/modeling_roberta.py
+++ b/pytorch_transformers/modeling_roberta.py
@@ -98,15 +98,15 @@ ROBERTA_INPUTS_DOCSTRING = r"""
Inputs:
**input_ids**: ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
Indices of input sequence tokens in the vocabulary.
- To match pre-training, RoBERTa input sequence should be formatted with [CLS] and [SEP] tokens as follows:
+ To match pre-training, RoBERTa input sequence should be formatted with and tokens as follows:
(a) For sequence pairs:
- ``tokens: [CLS] is this jack ##son ##ville ? [SEP][SEP] no it is not . [SEP]``
+ ``tokens: Is this Jacksonville ? No it is not . ``
(b) For single sequences:
- ``tokens: [CLS] the dog is hairy . [SEP]``
+ ``tokens: the dog is hairy . ``
Fully encoded sequences or sequence pairs can be obtained using the RobertaTokenizer.encode function with
the ``add_special_tokens`` parameter set to ``True``.
diff --git a/pytorch_transformers/tokenization_roberta.py b/pytorch_transformers/tokenization_roberta.py
index edf4717c..13d963d4 100644
--- a/pytorch_transformers/tokenization_roberta.py
+++ b/pytorch_transformers/tokenization_roberta.py
@@ -163,14 +163,14 @@ class RobertaTokenizer(PreTrainedTokenizer):
def add_special_tokens_single_sentence(self, token_ids):
"""
Adds special tokens to a sequence for sequence classification tasks.
- A RoBERTa sequence has the following format: [CLS] X [SEP]
+ A RoBERTa sequence has the following format: X
"""
return [self._convert_token_to_id(self.cls_token)] + token_ids + [self._convert_token_to_id(self.sep_token)]
def add_special_tokens_sentences_pair(self, token_ids_0, token_ids_1):
"""
Adds special tokens to a sequence pair for sequence classification tasks.
- A RoBERTa sequence pair has the following format: [CLS] A [SEP][SEP] B [SEP]
+ A RoBERTa sequence pair has the following format: A B
"""
sep = [self._convert_token_to_id(self.sep_token)]
cls = [self._convert_token_to_id(self.cls_token)]