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* Add a script to check all models are tested and documented * Apply suggestions from code review Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> * Address comments Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>
126 lines
3.6 KiB
ReStructuredText
126 lines
3.6 KiB
ReStructuredText
CamemBERT
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Overview
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~~~~~~~~~~~~~~~~~~~~~
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The CamemBERT model was proposed in `CamemBERT: a Tasty French Language Model <https://arxiv.org/abs/1911.03894>`__
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by Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric Villemonte de la
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Clergerie, Djamé Seddah, and Benoît Sagot. It is based on Facebook's RoBERTa model released in 2019. It is a model
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trained on 138GB of French text.
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The abstract from the paper is the following:
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*Pretrained language models are now ubiquitous in Natural Language Processing. Despite their success,
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most available models have either been trained on English data or on the concatenation of data in multiple
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languages. This makes practical use of such models --in all languages except English-- very limited. Aiming
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to address this issue for French, we release CamemBERT, a French version of the Bi-directional Encoders for
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Transformers (BERT). We measure the performance of CamemBERT compared to multilingual models in multiple
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downstream tasks, namely part-of-speech tagging, dependency parsing, named-entity recognition, and natural
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language inference. CamemBERT improves the state of the art for most of the tasks considered. We release the
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pretrained model for CamemBERT hoping to foster research and downstream applications for French NLP.*
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Tips:
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- This implementation is the same as RoBERTa. Refer to the `documentation of RoBERTa <./roberta.html>`__ for usage
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examples as well as the information relative to the inputs and outputs.
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The original code can be found `here <https://camembert-model.fr/>`_.
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CamembertConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertConfig
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:members:
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CamembertTokenizer
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertTokenizer
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:members: build_inputs_with_special_tokens, get_special_tokens_mask,
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create_token_type_ids_from_sequences, save_vocabulary
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CamembertModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertModel
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:members:
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CamembertForMaskedLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertForMaskedLM
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:members:
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CamembertForSequenceClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertForSequenceClassification
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:members:
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CamembertForMultipleChoice
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertForMultipleChoice
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:members:
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CamembertForTokenClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertForTokenClassification
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:members:
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CamembertForQuestionAnswering
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.CamembertForQuestionAnswering
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:members:
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TFCamembertModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFCamembertModel
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:members:
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TFCamembertForMaskedLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFCamembertForMaskedLM
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:members:
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TFCamembertForSequenceClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFCamembertForSequenceClassification
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:members:
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TFCamembertForMultipleChoice
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFCamembertForMultipleChoice
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:members:
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TFCamembertForTokenClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFCamembertForTokenClassification
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:members:
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TFCamembertForQuestionAnswering
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFCamembertForQuestionAnswering
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:members: |