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transformers/docs/source/en/model_doc/camembert.md
Steven Liu c0f8d055ce
[docs] Redesign (#31757) 
* toctree

* not-doctested.txt

* collapse sections

* feedback

* update

* rewrite get started sections

* fixes

* fix

* loading models

* fix

* customize models

* share

* fix link

* contribute part 1

* contribute pt 2

* fix toctree

* tokenization pt 1

* Add new model (#32615)

* v1 - working version

* fix

* fix

* fix

* fix

* rename to correct name

* fix title

* fixup

* rename files

* fix

* add copied from on tests

* rename to `FalconMamba` everywhere and fix bugs

* fix quantization + accelerate

* fix copies

* add `torch.compile` support

* fix tests

* fix tests and add slow tests

* copies on config

* merge the latest changes

* fix tests

* add few lines about instruct

* Apply suggestions from code review

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix

* fix tests

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* "to be not" -> "not to be" (#32636)

* "to be not" -> "not to be"

* Update sam.md

* Update trainer.py

* Update modeling_utils.py

* Update test_modeling_utils.py

* Update test_modeling_utils.py

* fix hfoption tag

* tokenization pt. 2

* image processor

* fix toctree

* backbones

* feature extractor

* fix file name

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* update

* make style

* fix toctree

* revision

* make fixup

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* fix

* make style

* fix hfoption tag

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* pipeline gradio

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* add pipeline

* fix toctree

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* fix toctree

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* cache

* text generation

* fix

* chat pipeline

* chat stuff

* xla

* torch.compile

* cpu inference

* toctree

* gpu inference

* agents and tools

* gguf/tiktoken

* finetune

* toctree

* trainer

* trainer pt 2

* optims

* optimizers

* accelerate

* parallelism

* fsdp

* update

* distributed cpu

* hardware training

* gpu training

* gpu training 2

* peft

* distrib debug

* deepspeed 1

* deepspeed 2

* chat toctree

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* quant pt 2

* fix toctree

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* fix

* quant pt 3

* quant pt 4

* serialization

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* fix

* all frameworks

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* supported model frameworks

* flashattention

* rm check_table

* not-doctested.txt

* rm check_support_list.py

* feedback

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* update

* feedback

* updates

* update

---------

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
2025-03-03 10:33:46 -08:00

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CamemBERT

PyTorch TensorFlow SDPA

Overview

The CamemBERT model was proposed in CamemBERT: a Tasty French Language Model by Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric Villemonte de la Clergerie, Djamé Seddah, and Benoît Sagot. It is based on Facebook's RoBERTa model released in 2019. It is a model trained on 138GB of French text.

The abstract from the paper is the following:

Pretrained language models are now ubiquitous in Natural Language Processing. Despite their success, most available models have either been trained on English data or on the concatenation of data in multiple languages. This makes practical use of such models --in all languages except English-- very limited. Aiming to address this issue for French, we release CamemBERT, a French version of the Bi-directional Encoders for Transformers (BERT). We measure the performance of CamemBERT compared to multilingual models in multiple downstream tasks, namely part-of-speech tagging, dependency parsing, named-entity recognition, and natural language inference. CamemBERT improves the state of the art for most of the tasks considered. We release the pretrained model for CamemBERT hoping to foster research and downstream applications for French NLP.

This model was contributed by the ALMAnaCH team (Inria). The original code can be found here.

This implementation is the same as RoBERTa. Refer to the documentation of RoBERTa for usage examples as well as the information relative to the inputs and outputs.

Resources

CamembertConfig

autodoc CamembertConfig

CamembertTokenizer

autodoc CamembertTokenizer - build_inputs_with_special_tokens - get_special_tokens_mask - create_token_type_ids_from_sequences - save_vocabulary

CamembertTokenizerFast

autodoc CamembertTokenizerFast

CamembertModel

autodoc CamembertModel

CamembertForCausalLM

autodoc CamembertForCausalLM

CamembertForMaskedLM

autodoc CamembertForMaskedLM

CamembertForSequenceClassification

autodoc CamembertForSequenceClassification

CamembertForMultipleChoice

autodoc CamembertForMultipleChoice

CamembertForTokenClassification

autodoc CamembertForTokenClassification

CamembertForQuestionAnswering

autodoc CamembertForQuestionAnswering

TFCamembertModel

autodoc TFCamembertModel

TFCamembertForCausalLM

autodoc TFCamembertForCausalLM

TFCamembertForMaskedLM

autodoc TFCamembertForMaskedLM

TFCamembertForSequenceClassification

autodoc TFCamembertForSequenceClassification

TFCamembertForMultipleChoice

autodoc TFCamembertForMultipleChoice

TFCamembertForTokenClassification

autodoc TFCamembertForTokenClassification

TFCamembertForQuestionAnswering

autodoc TFCamembertForQuestionAnswering