FM / squeezebert

/usr/local/lib/python3.6/site-packages/transformers/models/squeezebert/

/usr/local/lib/python3.6/site-packages/transformers/models/squeezebert

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

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/squeezebert/__init__.py (2527B)

# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.

# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# 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.

from typing import TYPE_CHECKING

from ...utils import _LazyModule, is_tokenizers_available, is_torch_available

_import_structure = {
    "configuration_squeezebert": ["SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "SqueezeBertConfig"],
    "tokenization_squeezebert": ["SqueezeBertTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_squeezebert_fast"] = ["SqueezeBertTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_squeezebert"] = [
        "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SqueezeBertForMaskedLM",
        "SqueezeBertForMultipleChoice",
        "SqueezeBertForQuestionAnswering",
        "SqueezeBertForSequenceClassification",
        "SqueezeBertForTokenClassification",
        "SqueezeBertModel",
        "SqueezeBertModule",
        "SqueezeBertPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_squeezebert import SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, SqueezeBertConfig
    from .tokenization_squeezebert import SqueezeBertTokenizer

if is_tokenizers_available():
        from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

if is_torch_available():
        from .modeling_squeezebert import (
            SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            SqueezeBertForMaskedLM,
            SqueezeBertForMultipleChoice,
            SqueezeBertForQuestionAnswering,
            SqueezeBertForSequenceClassification,
            SqueezeBertForTokenClassification,
            SqueezeBertModel,
            SqueezeBertModule,
            SqueezeBertPreTrainedModel,
        )

else:
    import sys

sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

# flake8: noqa # There's no way to ignore "F401 '...' imported but unused" warnings in this # module, but to preserve other warnings. So, don't check this module at all. # Copyright 2020 The HuggingFace Team. All rights reserved. # # 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. from typing import TYPE_CHECKING from ...utils import _LazyModule, is_tokenizers_available, is_torch_available _import_structure = { "configuration_squeezebert": ["SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "SqueezeBertConfig"], "tokenization_squeezebert": ["SqueezeBertTokenizer"], } if is_tokenizers_available(): _import_structure["tokenization_squeezebert_fast"] = ["SqueezeBertTokenizerFast"] if is_torch_available(): _import_structure["modeling_squeezebert"] = [ "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST", "SqueezeBertForMaskedLM", "SqueezeBertForMultipleChoice", "SqueezeBertForQuestionAnswering", "SqueezeBertForSequenceClassification", "SqueezeBertForTokenClassification", "SqueezeBertModel", "SqueezeBertModule", "SqueezeBertPreTrainedModel", ] if TYPE_CHECKING: from .configuration_squeezebert import SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, SqueezeBertConfig from .tokenization_squeezebert import SqueezeBertTokenizer if is_tokenizers_available(): from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast if is_torch_available(): from .modeling_squeezebert import ( SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST, SqueezeBertForMaskedLM, SqueezeBertForMultipleChoice, SqueezeBertForQuestionAnswering, SqueezeBertForSequenceClassification, SqueezeBertForTokenClassification, SqueezeBertModel, SqueezeBertModule, SqueezeBertPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)