# coding=utf-8 # Copyright 2019 Inria, Facebook AI Research and the HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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. """PyTorch CamemBERT model. """ import logging from .configuration_camembert import CamembertConfig from .file_utils import add_start_docstrings from .modeling_roberta import ( RobertaForMaskedLM, RobertaForMultipleChoice, RobertaForQuestionAnswering, RobertaForSequenceClassification, RobertaForTokenClassification, RobertaModel, ) logger = logging.getLogger(__name__) CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP = { "camembert-base": "https://s3.amazonaws.com/models.huggingface.co/bert/camembert-base-pytorch_model.bin", "umberto-commoncrawl-cased-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/Musixmatch/umberto-commoncrawl-cased-v1/pytorch_model.bin", "umberto-wikipedia-uncased-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/Musixmatch/umberto-wikipedia-uncased-v1/pytorch_model.bin", } CAMEMBERT_START_DOCSTRING = r""" This model is a PyTorch `torch.nn.Module `_ sub-class. Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and behavior. Parameters: config (:class:`~transformers.CamembertConfig`): Model configuration class with all the parameters of the model. Initializing with a config file does not load the weights associated with the model, only the configuration. Check out the :meth:`~transformers.PreTrainedModel.from_pretrained` method to load the model weights. """ @add_start_docstrings( "The bare CamemBERT Model transformer outputting raw hidden-states without any specific head on top.", CAMEMBERT_START_DOCSTRING, ) class CamembertModel(RobertaModel): """ This class overrides :class:`~transformers.RobertaModel`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = CamembertConfig pretrained_model_archive_map = CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP @add_start_docstrings( """CamemBERT Model with a `language modeling` head on top. """, CAMEMBERT_START_DOCSTRING, ) class CamembertForMaskedLM(RobertaForMaskedLM): """ This class overrides :class:`~transformers.RobertaForMaskedLM`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = CamembertConfig pretrained_model_archive_map = CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP @add_start_docstrings( """CamemBERT Model transformer with a sequence classification/regression head on top (a linear layer on top of the pooled output) e.g. for GLUE tasks. """, CAMEMBERT_START_DOCSTRING, ) class CamembertForSequenceClassification(RobertaForSequenceClassification): """ This class overrides :class:`~transformers.RobertaForSequenceClassification`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = CamembertConfig pretrained_model_archive_map = CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP @add_start_docstrings( """CamemBERT Model with a multiple choice classification head on top (a linear layer on top of the pooled output and a softmax) e.g. for RocStories/SWAG tasks. """, CAMEMBERT_START_DOCSTRING, ) class CamembertForMultipleChoice(RobertaForMultipleChoice): """ This class overrides :class:`~transformers.RobertaForMultipleChoice`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = CamembertConfig pretrained_model_archive_map = CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP @add_start_docstrings( """CamemBERT Model with a token classification head on top (a linear layer on top of the hidden-states output) e.g. for Named-Entity-Recognition (NER) tasks. """, CAMEMBERT_START_DOCSTRING, ) class CamembertForTokenClassification(RobertaForTokenClassification): """ This class overrides :class:`~transformers.RobertaForTokenClassification`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = CamembertConfig pretrained_model_archive_map = CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP @add_start_docstrings( """CamemBERT Model with a span classification head on top for extractive question-answering tasks like SQuAD (a linear layers on top of the hidden-states output to compute `span start logits` and `span end logits` """, CAMEMBERT_START_DOCSTRING, ) class CamembertForQuestionAnswering(RobertaForQuestionAnswering): """ This class overrides :class:`~transformers.RobertaForQuestionAnswering`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = CamembertConfig pretrained_model_archive_map = CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_MAP