Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_squeezebert.py	6936	0644	editdlrm
modeling_squeezebert.py	45329	0644	editdlrm
tokenization_squeezebert.py	2277	0644	editdlrm
tokenization_squeezebert_fast.py	2928	0644	editdlrm
__init__.py	2527	0644	editdlrm

# coding=utf-8 # Copyright 2020 The SqueezeBert authors and The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tokenization classes for SqueezeBERT.""" from ...utils import logging from ..bert.tokenization_bert import BertTokenizer logger = logging.get_logger(__name__) VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt"} PRETRAINED_VOCAB_FILES_MAP = { "vocab_file": { "squeezebert/squeezebert-uncased": "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt", "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt", "squeezebert/squeezebert-mnli-headless": "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt", } } PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = { "squeezebert/squeezebert-uncased": 512, "squeezebert/squeezebert-mnli": 512, "squeezebert/squeezebert-mnli-headless": 512, } PRETRAINED_INIT_CONFIGURATION = { "squeezebert/squeezebert-uncased": {"do_lower_case": True}, "squeezebert/squeezebert-mnli": {"do_lower_case": True}, "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True}, } class SqueezeBertTokenizer(BertTokenizer): r""" Constructs a SqueezeBert tokenizer. [`SqueezeBertTokenizer`] is identical to [`BertTokenizer`] and runs end-to-end tokenization: punctuation splitting + wordpiece. Refer to superclass [`BertTokenizer`] for usage examples and documentation concerning parameters. """ vocab_files_names = VOCAB_FILES_NAMES pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES pretrained_init_configuration = PRETRAINED_INIT_CONFIGURATION