Update naming + remove f string in run_lm_finetuning example
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@@ -820,7 +820,7 @@ class PreTrainedTokenizer(object):
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{
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input_ids: list[int],
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overflowing_tokens: list[int] if a ``max_length`` is specified, else None
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sequence_ids: list[int] if ``add_special_tokens`` if set to ``True``
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special_tokens_mask: list[int] if ``add_special_tokens`` if set to ``True``
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}
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With the fields:
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@@ -828,7 +828,7 @@ class PreTrainedTokenizer(object):
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``overflowing_tokens``: list of overflowing tokens if a max length is specified.
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``sequence_ids``: if adding special tokens, this is a list of [0, 1], with 0 specifying special added
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``special_tokens_mask``: if adding special tokens, this is a list of [0, 1], with 0 specifying special added
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tokens and 1 specifying sequence tokens.
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"""
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pair = bool(pair_ids is not None)
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@@ -857,7 +857,7 @@ class PreTrainedTokenizer(object):
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if add_special_tokens:
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sequence = self.add_special_tokens_sequence_pair(ids, pair_ids) if pair else self.add_special_tokens_single_sequence(ids)
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token_type_ids = self.create_token_type_ids_from_sequences(ids, pair_ids) if pair else [0] * len(sequence)
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encoded_inputs["sequence_ids"] = self.get_sequence_ids(ids, pair_ids)
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encoded_inputs["special_tokens_mask"] = self.get_special_tokens_mask(ids, pair_ids)
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else:
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sequence = ids + pair_ids if pair else ids
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token_type_ids = [0] * len(ids) + ([1] * len(pair_ids) if pair else [])
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@@ -877,6 +877,7 @@ class PreTrainedTokenizer(object):
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if max_length and len(encoded_inputs["input_ids"]) > max_length:
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encoded_inputs["input_ids"] = encoded_inputs["input_ids"][:max_length]
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encoded_inputs["token_type_ids"] = encoded_inputs["token_type_ids"][:max_length]
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encoded_inputs["special_tokens_mask"] = encoded_inputs["special_tokens_mask"][:max_length]
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return encoded_inputs
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@@ -892,7 +893,7 @@ class PreTrainedTokenizer(object):
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logger.warning("This tokenizer does not make use of special tokens. The two sequences have been concatenated.")
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return token_ids_0 + token_ids_1
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def get_sequence_ids(self, token_ids_0, token_ids_1=None, special_tokens_present=False):
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def get_special_tokens_mask(self, token_ids_0, token_ids_1=None, special_tokens_present=False):
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return [1] * ((len(token_ids_1) if token_ids_1 else 0) + len(token_ids_0))
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def convert_ids_to_tokens(self, ids, skip_special_tokens=False):
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