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usr
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local
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lib
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python3.6
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site-packages
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transformers
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models
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qdqbert
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/usr/local/lib/python3.6/site-packages/transformers/models/qdqbert
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__pycache__/
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configuration_qdqbert.py
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dl
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modeling_qdqbert.py
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dl
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__init__.py
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dl
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Edit:
/usr/local/lib/python3.6/site-packages/transformers/models/qdqbert/__init__.py
(2300B)
# 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 2021 NVIDIA Corporation and 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_torch_available _import_structure = { "configuration_qdqbert": ["QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "QDQBertConfig"], } if is_torch_available(): _import_structure["modeling_qdqbert"] = [ "QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST", "QDQBertForMaskedLM", "QDQBertForMultipleChoice", "QDQBertForNextSentencePrediction", "QDQBertForQuestionAnswering", "QDQBertForSequenceClassification", "QDQBertForTokenClassification", "QDQBertLayer", "QDQBertLMHeadModel", "QDQBertModel", "QDQBertPreTrainedModel", "load_tf_weights_in_qdqbert", ] if TYPE_CHECKING: from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig if is_torch_available(): from .modeling_qdqbert import ( QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST, QDQBertForMaskedLM, QDQBertForMultipleChoice, QDQBertForNextSentencePrediction, QDQBertForQuestionAnswering, QDQBertForSequenceClassification, QDQBertForTokenClassification, QDQBertLayer, QDQBertLMHeadModel, QDQBertModel, QDQBertPreTrainedModel, load_tf_weights_in_qdqbert, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
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