FM / prophetnet

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_prophetnet.py	8285	0644	edit dl rm
convert_prophetnet_original_pytorch_checkpoint_to_pytorch.py	7055	0644	edit dl rm
modeling_prophetnet.py	113267	0644	edit dl rm
tokenization_prophetnet.py	12493	0644	edit dl rm
__init__.py	2048	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/prophetnet/__init__.py (2048B)

# 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_torch_available

_import_structure = {
    "configuration_prophetnet": ["PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ProphetNetConfig"],
    "tokenization_prophetnet": ["ProphetNetTokenizer"],
}

if is_torch_available():
    _import_structure["modeling_prophetnet"] = [
        "PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ProphetNetDecoder",
        "ProphetNetEncoder",
        "ProphetNetForCausalLM",
        "ProphetNetForConditionalGeneration",
        "ProphetNetModel",
        "ProphetNetPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
    from .tokenization_prophetnet import ProphetNetTokenizer

if is_torch_available():
        from .modeling_prophetnet import (
            PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            ProphetNetDecoder,
            ProphetNetEncoder,
            ProphetNetForCausalLM,
            ProphetNetForConditionalGeneration,
            ProphetNetModel,
            ProphetNetPreTrainedModel,
        )

else:
    import sys

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

cmd: