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* Reorganize doc for multilingual support * Fix style * Style * Toc trees * Adapt templates
110 lines
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110 lines
3.5 KiB
Plaintext
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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# FlauBERT
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## Overview
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The FlauBERT model was proposed in the paper [FlauBERT: Unsupervised Language Model Pre-training for French](https://arxiv.org/abs/1912.05372) by Hang Le et al. It's a transformer model pretrained using a masked language
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modeling (MLM) objective (like BERT).
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The abstract from the paper is the following:
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*Language models have become a key step to achieve state-of-the art results in many different Natural Language
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Processing (NLP) tasks. Leveraging the huge amount of unlabeled texts nowadays available, they provide an efficient way
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to pre-train continuous word representations that can be fine-tuned for a downstream task, along with their
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contextualization at the sentence level. This has been widely demonstrated for English using contextualized
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representations (Dai and Le, 2015; Peters et al., 2018; Howard and Ruder, 2018; Radford et al., 2018; Devlin et al.,
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2019; Yang et al., 2019b). In this paper, we introduce and share FlauBERT, a model learned on a very large and
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heterogeneous French corpus. Models of different sizes are trained using the new CNRS (French National Centre for
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Scientific Research) Jean Zay supercomputer. We apply our French language models to diverse NLP tasks (text
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classification, paraphrasing, natural language inference, parsing, word sense disambiguation) and show that most of the
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time they outperform other pretraining approaches. Different versions of FlauBERT as well as a unified evaluation
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protocol for the downstream tasks, called FLUE (French Language Understanding Evaluation), are shared to the research
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community for further reproducible experiments in French NLP.*
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This model was contributed by [formiel](https://huggingface.co/formiel). The original code can be found [here](https://github.com/getalp/Flaubert).
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## FlaubertConfig
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[[autodoc]] FlaubertConfig
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## FlaubertTokenizer
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[[autodoc]] FlaubertTokenizer
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## FlaubertModel
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[[autodoc]] FlaubertModel
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- forward
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## FlaubertWithLMHeadModel
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[[autodoc]] FlaubertWithLMHeadModel
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- forward
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## FlaubertForSequenceClassification
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[[autodoc]] FlaubertForSequenceClassification
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- forward
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## FlaubertForMultipleChoice
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[[autodoc]] FlaubertForMultipleChoice
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- forward
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## FlaubertForTokenClassification
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[[autodoc]] FlaubertForTokenClassification
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- forward
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## FlaubertForQuestionAnsweringSimple
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[[autodoc]] FlaubertForQuestionAnsweringSimple
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- forward
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## FlaubertForQuestionAnswering
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[[autodoc]] FlaubertForQuestionAnswering
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- forward
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## TFFlaubertModel
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[[autodoc]] TFFlaubertModel
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- call
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## TFFlaubertWithLMHeadModel
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[[autodoc]] TFFlaubertWithLMHeadModel
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- call
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## TFFlaubertForSequenceClassification
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[[autodoc]] TFFlaubertForSequenceClassification
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- call
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## TFFlaubertForMultipleChoice
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[[autodoc]] TFFlaubertForMultipleChoice
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- call
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## TFFlaubertForTokenClassification
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[[autodoc]] TFFlaubertForTokenClassification
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- call
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## TFFlaubertForQuestionAnsweringSimple
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[[autodoc]] TFFlaubertForQuestionAnsweringSimple
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- call
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