/usr/local/lib/python3.6/site-packages/transformers/models/xlm_prophetnet
NameSizeModeActions
__pycache__/-0755rm
configuration_xlm_prophetnet.py12420644editdlrm
modeling_xlm_prophetnet.py71690644editdlrm
tokenization_xlm_prophetnet.py138830644editdlrm
__init__.py21990644editdlrm
Edit: /usr/local/lib/python3.6/site-packages/transformers/models/xlm_prophetnet/__init__.py (2199B)
# 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_sentencepiece_available, is_torch_available _import_structure = { "configuration_xlm_prophetnet": [ "XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig", ], } if is_sentencepiece_available(): _import_structure["tokenization_xlm_prophetnet"] = ["XLMProphetNetTokenizer"] if is_torch_available(): _import_structure["modeling_xlm_prophetnet"] = [ "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST", "XLMProphetNetDecoder", "XLMProphetNetEncoder", "XLMProphetNetForCausalLM", "XLMProphetNetForConditionalGeneration", "XLMProphetNetModel", ] if TYPE_CHECKING: from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig if is_sentencepiece_available(): from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer if is_torch_available(): from .modeling_xlm_prophetnet import ( XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST, XLMProphetNetDecoder, XLMProphetNetEncoder, XLMProphetNetForCausalLM, XLMProphetNetForConditionalGeneration, XLMProphetNetModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)