mirror of
https://github.com/huggingface/transformers.git
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* maskformer * conflicts * conflicts * minor fixes * feature extractor test fix refactor MaskFormerLoss following conversation MaskFormer related types should not trigger a module time import error missed one removed all the types that are not used update config mapping minor updates in the doc resolved conversation that doesn't need a discussion minor changes resolved conversations fixed DetrDecoder * minor changes minor changes fixed mdx file test feature_extractor return types functional losses -> classes removed the return type test for the feature extractor minor changes + style + quality * conflicts? * rebase master * readme * added missing files * deleded poolformers test that where in the wrong palce * CI * minor changes * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * resolved conversations * minor changes * conversations [Unispeech] Fix slow tests (#15818) * remove soundfile old way of loading audio * Adapt slow test [Barthez Tokenizer] Fix saving (#15815) [TFXLNet] Correct tf xlnet generate (#15822) * [TFXLNet] Correct tf xlnet * adapt test comment Fix the push run (#15807) Fix semantic segmentation pipeline test (#15826) Fix dummy_inputs() to dummy_inputs in symbolic_trace doc (#15776) Add model specific output classes to PoolFormer model docs (#15746) * Added model specific output classes to poolformer docs * Fixed Segformer typo in Poolformer docs Adding the option to return_timestamps on pure CTC ASR models. (#15792) * Adding the option to return_timestamps on pure CTC ASR models. * Remove `math.prod` which was introduced in Python 3.8 * int are not floats. * Reworking the PR to support "char" vs "word" output. * Fixup! * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Quality. Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> HFTracer.trace should use/return self.graph to be compatible with torch.fx.Tracer (#15824) Fix tf.concatenate + test past_key_values for TF models (#15774) * fix wrong method name tf.concatenate * add tests related to causal LM / decoder * make style and quality * clean-up * Fix TFBertModel's extended_attention_mask when past_key_values is provided * Fix tests * fix copies * More tf.int8 -> tf.int32 in TF test template * clean-up * Update TF test template * revert the previous commit + update the TF test template * Fix TF template extended_attention_mask when past_key_values is provided * Fix some styles manually * clean-up * Fix ValueError: too many values to unpack in the test * Fix more: too many values to unpack in the test * Add a comment for extended_attention_mask when there is past_key_values * Fix TFElectra extended_attention_mask when past_key_values is provided * Add tests to other TF models * Fix for TF Electra test: add prepare_config_and_inputs_for_decoder * Fix not passing training arg to lm_head in TFRobertaForCausalLM * Fix tests (with past) for TF Roberta * add testing for pask_key_values for TFElectra model Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> [examples/summarization and translation] fix readme (#15833) Add ONNX Runtime quantization for text classification notebook (#15817) Re-enable doctests for the quicktour (#15828) * Re-enable doctests for the quicktour * Re-enable doctests for task_summary (#15830) * Remove & Framework split model report (#15825) Add TFConvNextModel (#15750) * feat: initial implementation of convnext in tensorflow. * fix: sample code for the classification model. * chore: added checked for from the classification model. * chore: set bias initializer in the classification head. * chore: updated license terms. * chore: removed ununsed imports * feat: enabled argument during using drop_path. * chore: replaced tf.identity with layers.Activation(linear). * chore: edited default checkpoint. * fix: minor bugs in the initializations. * partial-fix: tf model errors for loading pretrained pt weights. * partial-fix: call method updated * partial-fix: cross loading of weights (4x3 variables to be matched) * chore: removed unneeded comment. * removed playground.py * rebasing * rebasing and removing playground.py. * fix: renaming TFConvNextStage conv and layer norm layers * chore: added initializers and other minor additions. * chore: added initializers and other minor additions. * add: tests for convnext. * fix: integration tester class. * fix: issues mentioned in pr feedback (round 1). * fix: how output_hidden_states arg is propoagated inside the network. * feat: handling of arg for pure cnn models. * chore: added a note on equal contribution in model docs. * rebasing * rebasing and removing playground.py. * feat: encapsulation for the convnext trunk. * Fix variable naming; Test-related corrections; Run make fixup * chore: added Joao as a contributor to convnext. * rebasing * rebasing and removing playground.py. * rebasing * rebasing and removing playground.py. * chore: corrected copyright year and added comment on NHWC. * chore: fixed the black version and ran formatting. * chore: ran make style. * chore: removed from_pt argument from test, ran make style. * rebasing * rebasing and removing playground.py. * rebasing * rebasing and removing playground.py. * fix: tests in the convnext subclass, ran make style. * rebasing * rebasing and removing playground.py. * rebasing * rebasing and removing playground.py. * chore: moved convnext test to the correct location * fix: locations for the test file of convnext. * fix: convnext tests. * chore: applied sgugger's suggestion for dealing w/ output_attentions. * chore: added comments. * chore: applied updated quality enviornment style. * chore: applied formatting with quality enviornment. * chore: revert to the previous tests/test_modeling_common.py. * chore: revert to the original test_modeling_common.py * chore: revert to previous states for test_modeling_tf_common.py and modeling_tf_utils.py * fix: tests for convnext. * chore: removed output_attentions argument from convnext config. * chore: revert to the earlier tf utils. * fix: output shapes of the hidden states * chore: removed unnecessary comment * chore: reverting to the right test_modeling_tf_common.py. * Styling nits Co-authored-by: ariG23498 <aritra.born2fly@gmail.com> Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com> * minor changes * doc fix in feature extractor * doc * typose * removed detr logic from config * removed detr logic from config * removed num_labels * small fix in the config * auxilary -> auxiliary * make style * some test is failing * fix a weird char in config prevending doc-builder * retry to fix the doc-builder issue * make style * new try to fix the doc builder * CI * change weights to facebook Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: ariG23498 <aritra.born2fly@gmail.com> Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
377 lines
10 KiB
YAML
377 lines
10 KiB
YAML
- sections:
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- local: index
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title: 🤗 Transformers
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- local: quicktour
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title: Quick tour
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- local: installation
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title: Installation
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- local: philosophy
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title: Philosophy
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- local: glossary
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title: Glossary
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title: Get started
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- sections:
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- local: pipeline_tutorial
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title: Pipelines for inference
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- local: autoclass_tutorial
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title: Load pretrained instances with an AutoClass
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- local: preprocessing
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title: Preprocess
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- local: task_summary
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title: Summary of the tasks
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- local: model_summary
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title: Summary of the models
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- local: training
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title: Fine-tuning a pretrained model
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- local: accelerate
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title: Distributed training with 🤗 Accelerate
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- local: model_sharing
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title: Share a model
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- local: tokenizer_summary
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title: Summary of the tokenizers
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- local: multilingual
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title: Multi-lingual models
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title: Tutorials
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- sections:
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- local: create_a_model
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title: Create a custom model
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- local: multilingual
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title: Inference for multilingual models
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- local: examples
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title: Examples
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- local: troubleshooting
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title: Troubleshooting
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- local: custom_datasets
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title: Fine-tuning with custom datasets
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- sections:
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- local: tasks/sequence_classification
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title: Text classification
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- local: tasks/token_classification
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title: Token classification
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- local: tasks/question_answering
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title: Question answering
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- local: tasks/language_modeling
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title: Language modeling
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- local: tasks/translation
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title: Translation
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- local: tasks/summarization
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title: Summarization
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- local: tasks/multiple_choice
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title: Multiple choice
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title: Fine-tune for downstream tasks
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- local: notebooks
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title: "🤗 Transformers Notebooks"
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- local: sagemaker
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title: Run training on Amazon SageMaker
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- local: community
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title: Community
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- local: converting_tensorflow_models
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title: Converting Tensorflow Checkpoints
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- local: migration
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title: Migrating from previous packages
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- local: contributing
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title: How to contribute to transformers?
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- local: add_new_model
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title: "How to add a model to 🤗 Transformers?"
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- local: add_new_pipeline
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title: "How to add a pipeline to 🤗 Transformers?"
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- local: fast_tokenizers
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title: "Using tokenizers from 🤗 Tokenizers"
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- local: performance
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title: 'Performance and Scalability: How To Fit a Bigger Model and Train It Faster'
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- local: parallelism
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title: Model Parallelism
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- local: testing
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title: Testing
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- local: debugging
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title: Debugging
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- local: serialization
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title: Exporting 🤗 Transformers models
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- local: custom_models
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title: Sharing custom models
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- local: pr_checks
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title: Checks on a Pull Request
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title: How-to guides
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- sections:
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- local: bertology
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title: BERTology
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- local: perplexity
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title: Perplexity of fixed-length models
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- local: benchmarks
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title: Benchmarks
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title: Research
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- sections:
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- sections:
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- local: main_classes/callback
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title: Callbacks
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- local: main_classes/configuration
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title: Configuration
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- local: main_classes/data_collator
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title: Data Collator
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- local: main_classes/keras_callbacks
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title: Keras callbacks
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- local: main_classes/logging
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title: Logging
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- local: main_classes/model
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title: Models
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- local: main_classes/onnx
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title: ONNX
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- local: main_classes/optimizer_schedules
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title: Optimization
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- local: main_classes/output
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title: Model outputs
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- local: main_classes/pipelines
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title: Pipelines
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- local: main_classes/processors
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title: Processors
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- local: main_classes/tokenizer
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title: Tokenizer
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- local: main_classes/trainer
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title: Trainer
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- local: main_classes/deepspeed
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title: DeepSpeed Integration
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- local: main_classes/feature_extractor
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title: Feature Extractor
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title: Main Classes
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- sections:
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- local: model_doc/albert
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title: ALBERT
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- local: model_doc/auto
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title: Auto Classes
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- local: model_doc/bart
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title: BART
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- local: model_doc/barthez
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title: BARThez
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- local: model_doc/bartpho
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title: BARTpho
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- local: model_doc/beit
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title: BEiT
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- local: model_doc/bert
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title: BERT
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- local: model_doc/bertweet
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title: Bertweet
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- local: model_doc/bert-generation
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title: BertGeneration
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- local: model_doc/bert-japanese
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title: BertJapanese
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- local: model_doc/big_bird
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title: BigBird
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- local: model_doc/bigbird_pegasus
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title: BigBirdPegasus
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- local: model_doc/blenderbot
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title: Blenderbot
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- local: model_doc/blenderbot-small
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title: Blenderbot Small
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- local: model_doc/bort
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title: BORT
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- local: model_doc/byt5
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title: ByT5
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- local: model_doc/camembert
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title: CamemBERT
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- local: model_doc/canine
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title: CANINE
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- local: model_doc/convnext
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title: ConvNeXT
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- local: model_doc/clip
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title: CLIP
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- local: model_doc/convbert
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title: ConvBERT
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- local: model_doc/cpm
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title: CPM
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- local: model_doc/ctrl
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title: CTRL
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- local: model_doc/data2vec
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title: Data2Vec
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- local: model_doc/deberta
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title: DeBERTa
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- local: model_doc/deberta-v2
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title: DeBERTa-v2
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- local: model_doc/deit
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title: DeiT
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- local: model_doc/detr
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title: DETR
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- local: model_doc/dialogpt
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title: DialoGPT
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- local: model_doc/distilbert
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title: DistilBERT
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- local: model_doc/dpr
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title: DPR
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- local: model_doc/electra
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title: ELECTRA
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- local: model_doc/encoder-decoder
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title: Encoder Decoder Models
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- local: model_doc/flaubert
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title: FlauBERT
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- local: model_doc/fnet
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title: FNet
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- local: model_doc/fsmt
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title: FSMT
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- local: model_doc/funnel
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title: Funnel Transformer
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- local: model_doc/herbert
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title: HerBERT
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- local: model_doc/ibert
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title: I-BERT
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- local: model_doc/imagegpt
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title: ImageGPT
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- local: model_doc/layoutlm
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title: LayoutLM
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- local: model_doc/layoutlmv2
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title: LayoutLMV2
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- local: model_doc/layoutxlm
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title: LayoutXLM
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- local: model_doc/led
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title: LED
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- local: model_doc/longformer
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title: Longformer
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- local: model_doc/luke
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title: LUKE
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- local: model_doc/lxmert
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title: LXMERT
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- local: model_doc/marian
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title: MarianMT
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- local: model_doc/maskformer
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title: MaskFormer
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- local: model_doc/m2m_100
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title: M2M100
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- local: model_doc/mbart
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title: MBart and MBart-50
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- local: model_doc/megatron-bert
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title: MegatronBERT
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- local: model_doc/megatron_gpt2
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title: MegatronGPT2
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- local: model_doc/mluke
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title: MLUKE
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- local: model_doc/mobilebert
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title: MobileBERT
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- local: model_doc/mluke
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title: mLUKE
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- local: model_doc/mpnet
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title: MPNet
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- local: model_doc/mt5
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title: MT5
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- local: model_doc/nystromformer
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title: Nyströmformer
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- local: model_doc/openai-gpt
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title: OpenAI GPT
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- local: model_doc/gpt2
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title: OpenAI GPT2
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- local: model_doc/gptj
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title: GPT-J
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- local: model_doc/gpt_neo
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title: GPT Neo
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- local: model_doc/hubert
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title: Hubert
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- local: model_doc/perceiver
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title: Perceiver
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- local: model_doc/pegasus
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title: Pegasus
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- local: model_doc/phobert
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title: PhoBERT
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- local: model_doc/plbart
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title: PLBart
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- local: model_doc/poolformer
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title: PoolFormer
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- local: model_doc/prophetnet
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title: ProphetNet
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- local: model_doc/qdqbert
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title: QDQBert
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- local: model_doc/rag
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title: RAG
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- local: model_doc/realm
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title: REALM
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- local: model_doc/reformer
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title: Reformer
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- local: model_doc/rembert
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title: RemBERT
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- local: model_doc/retribert
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title: RetriBERT
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- local: model_doc/roberta
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title: RoBERTa
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- local: model_doc/roformer
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title: RoFormer
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- local: model_doc/segformer
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title: SegFormer
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- local: model_doc/sew
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title: SEW
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- local: model_doc/sew-d
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title: SEW-D
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- local: model_doc/speech-encoder-decoder
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title: Speech Encoder Decoder Models
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- local: model_doc/speech_to_text
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title: Speech2Text
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- local: model_doc/speech_to_text_2
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title: Speech2Text2
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- local: model_doc/splinter
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title: Splinter
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- local: model_doc/squeezebert
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title: SqueezeBERT
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- local: model_doc/swin
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title: Swin Transformer
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- local: model_doc/t5
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title: T5
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- local: model_doc/t5v1.1
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title: T5v1.1
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- local: model_doc/tapas
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title: TAPAS
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- local: model_doc/transfo-xl
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title: Transformer XL
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- local: model_doc/trocr
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title: TrOCR
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- local: model_doc/unispeech
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title: UniSpeech
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- local: model_doc/unispeech-sat
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title: UniSpeech-SAT
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- local: model_doc/vilt
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title: ViLT
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- local: model_doc/vision-encoder-decoder
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title: Vision Encoder Decoder Models
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- local: model_doc/vision-text-dual-encoder
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title: Vision Text Dual Encoder
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- local: model_doc/vit
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title: Vision Transformer (ViT)
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- local: model_doc/vit_mae
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title: ViTMAE
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- local: model_doc/visual_bert
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title: VisualBERT
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- local: model_doc/wav2vec2
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title: Wav2Vec2
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- local: model_doc/wav2vec2_phoneme
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title: Wav2Vec2Phoneme
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- local: model_doc/wavlm
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title: WavLM
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- local: model_doc/xglm
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title: XGLM
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- local: model_doc/xlm
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title: XLM
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- local: model_doc/xlm-prophetnet
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title: XLM-ProphetNet
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- local: model_doc/xlm-roberta
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title: XLM-RoBERTa
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- local: model_doc/xlm-roberta-xl
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title: XLM-RoBERTa-XL
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- local: model_doc/xlnet
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title: XLNet
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- local: model_doc/xlsr_wav2vec2
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title: XLSR-Wav2Vec2
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- local: model_doc/xls_r
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title: XLS-R
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- local: model_doc/yoso
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title: YOSO
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title: Models
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- sections:
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- local: internal/modeling_utils
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title: Custom Layers and Utilities
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- local: internal/pipelines_utils
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title: Utilities for pipelines
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- local: internal/tokenization_utils
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title: Utilities for Tokenizers
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- local: internal/trainer_utils
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title: Utilities for Trainer
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- local: internal/generation_utils
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title: Utilities for Generation
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- local: internal/file_utils
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title: General Utilities
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title: Internal Helpers
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title: API
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