mirror of
https://github.com/huggingface/transformers.git
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* add distribution head to forecasting
* formatting
* Add generate function for forecasting
* Add generate function to prediction task
* formatting
* use argsort
* add past_observed_mask ordering
* fix arguments
* docs
* add back test_model_outputs_equivalence test
* formatting
* cleanup
* formatting
* use ACT2CLS
* formatting
* fix add_start_docstrings decorator
* add distribution head and generate function to regression task
add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput.
* add distribution head and generate function to regression task
add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput.
* fix typos
* add forecast_masking
* fixed tests
* use set_seed
* fix doc test
* formatting
* Update docs/source/en/model_doc/patchtst.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* better var names
* rename PatchTSTTranspose
* fix argument names and docs string
* remove compute_num_patches and unused class
* remove assert
* renamed to PatchTSTMasking
* use num_labels for classification
* use num_labels
* use default num_labels from super class
* move model_type after docstring
* renamed PatchTSTForMaskPretraining
* bs -> batch_size
* more review fixes
* use hidden_state
* rename encoder layer and block class
* remove commented seed_number
* edit docstring
* Add docstring
* formatting
* use past_observed_mask
* doc suggestion
* make fix-copies
* use Args:
* add docstring
* add docstring
* change some variable names and add PatchTST before some class names
* formatting
* fix argument types
* fix tests
* change x variable to patch_input
* format
* formatting
* fix-copies
* Update tests/models/patchtst/test_modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* move loss to forward
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* formatting
* fix a bug when pre_norm is set to True
* output_hidden_states is set to False as default
* set pre_norm=True as default
* format docstring
* format
* output_hidden_states is None by default
* add missing docs
* better var names
* docstring: remove default to False in output_hidden_states
* change labels name to target_values in regression task
* format
* fix tests
* change to forecast_mask_ratios and random_mask_ratio
* change mask names
* change future_values to target_values param in the prediction class
* remove nn.Sequential and make PatchTSTBatchNorm class
* black
* fix argument name for prediction
* add output_attentions option
* add output_attentions to PatchTSTEncoder
* formatting
* Add attention output option to all classes
* Remove PatchTSTEncoderBlock
* create PatchTSTEmbedding class
* use config in PatchTSTPatchify
* Use config in PatchTSTMasking class
* add channel_attn_weights
* Add PatchTSTScaler class
* add output_attentions arg to test function
* format
* Update doc with image patchtst.md
* fix-copies
* rename Forecast <-> Prediction
* change name of a few parameters to match with PatchTSMixer.
* Remove *ForForecasting class to match with other time series models.
* make style
* Remove PatchTSTForForecasting in the test
* remove PatchTSTForForecastingOutput class
* change test_forecast_head to test_prediction_head
* style
* fix docs
* fix tests
* change num_labels to num_targets
* Remove PatchTSTTranspose
* remove arguments in PatchTSTMeanScaler
* remove arguments in PatchTSTStdScaler
* add config as an argument to all the scaler classes
* reformat
* Add norm_eps for batchnorm and layernorm
* reformat.
* reformat
* edit docstring
* update docstring
* change variable name pooling to pooling_type
* fix output_hidden_states as tuple
* fix bug when calling PatchTSTBatchNorm
* change stride to patch_stride
* create PatchTSTPositionalEncoding class and restructure the PatchTSTEncoder
* formatting
* initialize scalers with configs
* edit output_hidden_states
* style
* fix forecast_mask_patches doc string
* doc improvements
* move summary to the start
* typo
* fix docstring
* turn off masking when using prediction, regression, classification
* return scaled output
* adjust output when using distribution head
* remove _num_patches function in the config
* get config.num_patches from patchifier init
* add output_attentions docstring, remove tuple in output_hidden_states
* change SamplePatchTSTPredictionOutput and SamplePatchTSTRegressionOutput to SamplePatchTSTOutput
* remove print("model_class: ", model_class)
* change encoder_attention_heads to num_attention_heads
* change norm to norm_layer
* change encoder_layers to num_hidden_layers
* change shared_embedding to share_embedding, shared_projection to share_projection
* add output_attentions
* more robust check of norm_type
* change dropout_path to path_dropout
* edit docstring
* remove positional_encoding function and add _init_pe in PatchTSTPositionalEncoding
* edit shape of cls_token and initialize it
* add a check on the num_input_channels.
* edit head_dim in the Prediction class to allow the use of cls_token
* remove some positional_encoding_type options, remove learn_pe arg, initalize pe
* change Exception to ValueError
* format
* norm_type is "batchnorm"
* make style
* change cls_token shape
* Change forecast_mask_patches to num_mask_patches. Remove forecast_mask_ratios.
* Bring PatchTSTClassificationHead on top of PatchTSTForClassification
* change encoder_ffn_dim to ffn_dim and edit the docstring.
* update variable names to match with the config
* add generation tests
* change num_mask_patches to num_forecast_mask_patches
* Add examples explaining the use of these models
* make style
* Revert "Revert "[time series] Add PatchTST (#25927)" (#27486)"
This reverts commit 78f6ed6c70
.
* make style
* fix default std scaler's minimum_scale
* fix docstring
* close code blocks
* Update docs/source/en/model_doc/patchtst.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/patchtst/test_modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/configuration_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix tests
* add add_start_docstrings
* move examples to the forward's docstrings
* update prepare_batch
* update test
* fix test_prediction_head
* fix generation test
* use seed to create generator
* add output_hidden_states and config.num_patches
* add loc and scale args in PatchTSTForPredictionOutput
* edit outputs if if not return_dict
* use self.share_embedding to check instead checking type.
* remove seed
* make style
* seed is an optional int
* fix test
* generator device
* Fix assertTrue test
* swap order of items in outputs when return_dict=False.
* add mask_type and random_mask_ratio to unittest
* Update modeling_patchtst.py
* add add_start_docstrings for regression model
* make style
* update model path
* Edit the ValueError comment in forecast_masking
* update examples
* make style
* fix commented code
* update examples: remove config from from_pretrained call
* Edit example outputs
* Set default target_values to None
* remove config setting in regression example
* Update configuration_patchtst.py
* Update configuration_patchtst.py
* remove config from examples
* change default d_model and ffn_dim
* norm_eps default
* set has_attentions to Trye and define self.seq_length = self.num_patche
* update docstring
* change variable mask_input to do_mask_input
* fix blank space.
* change logger.debug to logger.warning.
* remove unused PATCHTST_INPUTS_DOCSTRING
* remove all_generative_model_classes
* set test_missing_keys=True
* remove undefined params in the docstring.
---------
Co-authored-by: nnguyen <nnguyen@us.ibm.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
790 lines
23 KiB
YAML
790 lines
23 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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title: Get started
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- sections:
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- local: pipeline_tutorial
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title: Run inference with pipelines
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- local: autoclass_tutorial
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title: Write portable code with AutoClass
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- local: preprocessing
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title: Preprocess data
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- local: training
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title: Fine-tune a pretrained model
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- local: run_scripts
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title: Train with a script
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- local: accelerate
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title: Set up distributed training with 🤗 Accelerate
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- local: peft
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title: Load and train adapters with 🤗 PEFT
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- local: model_sharing
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title: Share your model
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- local: transformers_agents
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title: Agents
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- local: llm_tutorial
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title: Generation with LLMs
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title: Tutorials
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- sections:
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- isExpanded: false
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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: Causal language modeling
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- local: tasks/masked_language_modeling
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title: Masked 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: Natural Language Processing
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- isExpanded: false
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sections:
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- local: tasks/audio_classification
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title: Audio classification
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- local: tasks/asr
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title: Automatic speech recognition
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title: Audio
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- isExpanded: false
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sections:
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- local: tasks/image_classification
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title: Image classification
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- local: tasks/semantic_segmentation
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title: Image segmentation
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- local: tasks/video_classification
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title: Video classification
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- local: tasks/object_detection
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title: Object detection
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- local: tasks/zero_shot_object_detection
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title: Zero-shot object detection
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- local: tasks/zero_shot_image_classification
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title: Zero-shot image classification
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- local: tasks/monocular_depth_estimation
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title: Depth estimation
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- local: tasks/image_to_image
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title: Image-to-Image
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- local: tasks/knowledge_distillation_for_image_classification
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title: Knowledge Distillation for Computer Vision
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title: Computer Vision
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- isExpanded: false
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sections:
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- local: tasks/image_captioning
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title: Image captioning
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- local: tasks/document_question_answering
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title: Document Question Answering
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- local: tasks/visual_question_answering
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title: Visual Question Answering
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- local: tasks/text-to-speech
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title: Text to speech
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title: Multimodal
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- isExpanded: false
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sections:
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- local: generation_strategies
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title: Customize the generation strategy
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title: Generation
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- isExpanded: false
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sections:
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- local: tasks/idefics
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title: Image tasks with IDEFICS
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- local: tasks/prompting
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title: LLM prompting guide
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title: Prompting
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title: Task Guides
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- sections:
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- local: fast_tokenizers
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title: Use fast tokenizers from 🤗 Tokenizers
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- local: multilingual
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title: Run inference with multilingual models
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- local: create_a_model
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title: Use model-specific APIs
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- local: custom_models
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title: Share a custom model
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- local: chat_templating
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title: Templates for chat models
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- local: sagemaker
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title: Run training on Amazon SageMaker
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- local: serialization
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title: Export to ONNX
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- local: tflite
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title: Export to TFLite
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- local: torchscript
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title: Export to TorchScript
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- local: benchmarks
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title: Benchmarks
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- local: notebooks
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title: Notebooks with examples
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- local: community
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title: Community resources
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- local: custom_tools
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title: Custom Tools and Prompts
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- local: troubleshooting
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title: Troubleshoot
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title: Developer guides
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- sections:
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- local: performance
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title: Overview
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- local: quantization
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title: Quantization
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- sections:
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- local: perf_train_gpu_one
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title: Methods and tools for efficient training on a single GPU
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- local: perf_train_gpu_many
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title: Multiple GPUs and parallelism
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- local: perf_train_cpu
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title: Efficient training on CPU
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- local: perf_train_cpu_many
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title: Distributed CPU training
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- local: perf_train_tpu
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title: Training on TPUs
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- local: perf_train_tpu_tf
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title: Training on TPU with TensorFlow
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- local: perf_train_special
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title: Training on Specialized Hardware
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- local: perf_hardware
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title: Custom hardware for training
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- local: hpo_train
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title: Hyperparameter Search using Trainer API
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title: Efficient training techniques
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- sections:
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- local: perf_infer_cpu
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title: CPU inference
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- local: perf_infer_gpu_one
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title: GPU inference
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title: Optimizing inference
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- local: big_models
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title: Instantiating a big model
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- local: debugging
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title: Troubleshooting
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- local: tf_xla
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title: XLA Integration for TensorFlow Models
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- local: perf_torch_compile
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title: Optimize inference using `torch.compile()`
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title: Performance and scalability
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- sections:
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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_tensorflow_model
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title: How to convert a 🤗 Transformers model to TensorFlow?
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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: testing
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title: Testing
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- local: pr_checks
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title: Checks on a Pull Request
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title: Contribute
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- sections:
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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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- local: task_summary
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title: What 🤗 Transformers can do
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- local: tasks_explained
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title: How 🤗 Transformers solve tasks
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- local: model_summary
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title: The Transformer model family
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- local: tokenizer_summary
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title: Summary of the tokenizers
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- local: attention
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title: Attention mechanisms
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- local: pad_truncation
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title: Padding and truncation
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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: pipeline_webserver
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title: Pipelines for webserver inference
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- local: model_memory_anatomy
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title: Model training anatomy
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- local: llm_tutorial_optimization
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title: Getting the most out of LLMs
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title: Conceptual guides
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- sections:
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- sections:
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- local: main_classes/agent
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title: Agents and Tools
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- local: model_doc/auto
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title: Auto Classes
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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/text_generation
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title: Text Generation
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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/quantization
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title: Quantization
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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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- local: main_classes/image_processor
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title: Image Processor
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title: Main Classes
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- sections:
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- isExpanded: false
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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/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/bert
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title: BERT
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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/bertweet
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title: Bertweet
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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/biogpt
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title: BioGpt
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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/bloom
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title: BLOOM
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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/codegen
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title: CodeGen
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- local: model_doc/code_llama
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title: CodeLlama
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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/cpmant
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title: CPMANT
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- local: model_doc/ctrl
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title: CTRL
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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/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/ernie
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title: ERNIE
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- local: model_doc/ernie_m
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title: ErnieM
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- local: model_doc/esm
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title: ESM
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- local: model_doc/falcon
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title: Falcon
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- local: model_doc/flan-t5
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title: FLAN-T5
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- local: model_doc/flan-ul2
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title: FLAN-UL2
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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/fuyu
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title: Fuyu
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- local: model_doc/openai-gpt
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title: GPT
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- local: model_doc/gpt_neo
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title: GPT Neo
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- local: model_doc/gpt_neox
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title: GPT NeoX
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- local: model_doc/gpt_neox_japanese
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title: GPT NeoX Japanese
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- local: model_doc/gptj
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title: GPT-J
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- local: model_doc/gpt2
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title: GPT2
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- local: model_doc/gpt_bigcode
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title: GPTBigCode
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- local: model_doc/gptsan-japanese
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title: GPTSAN Japanese
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- local: model_doc/gpt-sw3
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title: GPTSw3
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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/jukebox
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title: Jukebox
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- local: model_doc/led
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title: LED
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- local: model_doc/llama
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title: LLaMA
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- local: model_doc/llama2
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title: Llama2
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- local: model_doc/longformer
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title: Longformer
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- local: model_doc/longt5
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title: LongT5
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- local: model_doc/luke
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title: LUKE
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- local: model_doc/m2m_100
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title: M2M100
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- local: model_doc/madlad-400
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title: MADLAD-400
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- local: model_doc/marian
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title: MarianMT
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- local: model_doc/markuplm
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title: MarkupLM
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- local: model_doc/mbart
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title: MBart and MBart-50
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- local: model_doc/mega
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title: MEGA
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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/mistral
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title: Mistral
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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/mpnet
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title: MPNet
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- local: model_doc/mpt
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title: MPT
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- local: model_doc/mra
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title: MRA
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- local: model_doc/mt5
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title: MT5
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- local: model_doc/mvp
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title: MVP
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- local: model_doc/nezha
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title: NEZHA
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- local: model_doc/nllb
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title: NLLB
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- local: model_doc/nllb-moe
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title: NLLB-MoE
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- local: model_doc/nystromformer
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title: Nyströmformer
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- local: model_doc/open-llama
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title: Open-Llama
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- local: model_doc/opt
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title: OPT
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- local: model_doc/pegasus
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title: Pegasus
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- local: model_doc/pegasus_x
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title: PEGASUS-X
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- local: model_doc/persimmon
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title: Persimmon
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- local: model_doc/phi
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title: Phi
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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/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
|
|
title: RetriBERT
|
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- local: model_doc/roberta
|
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title: RoBERTa
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- local: model_doc/roberta-prelayernorm
|
|
title: RoBERTa-PreLayerNorm
|
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- local: model_doc/roc_bert
|
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title: RoCBert
|
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- local: model_doc/roformer
|
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title: RoFormer
|
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- local: model_doc/rwkv
|
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title: RWKV
|
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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/switch_transformers
|
|
title: SwitchTransformers
|
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- local: model_doc/t5
|
|
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/tapex
|
|
title: TAPEX
|
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- local: model_doc/transfo-xl
|
|
title: Transformer XL
|
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- local: model_doc/ul2
|
|
title: UL2
|
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- local: model_doc/umt5
|
|
title: UMT5
|
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- local: model_doc/xmod
|
|
title: X-MOD
|
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- local: model_doc/xglm
|
|
title: XGLM
|
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- local: model_doc/xlm
|
|
title: XLM
|
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- local: model_doc/xlm-prophetnet
|
|
title: XLM-ProphetNet
|
|
- local: model_doc/xlm-roberta
|
|
title: XLM-RoBERTa
|
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- local: model_doc/xlm-roberta-xl
|
|
title: XLM-RoBERTa-XL
|
|
- local: model_doc/xlm-v
|
|
title: XLM-V
|
|
- local: model_doc/xlnet
|
|
title: XLNet
|
|
- local: model_doc/yoso
|
|
title: YOSO
|
|
title: Text models
|
|
- isExpanded: false
|
|
sections:
|
|
- local: model_doc/beit
|
|
title: BEiT
|
|
- local: model_doc/bit
|
|
title: BiT
|
|
- local: model_doc/conditional_detr
|
|
title: Conditional DETR
|
|
- local: model_doc/convnext
|
|
title: ConvNeXT
|
|
- local: model_doc/convnextv2
|
|
title: ConvNeXTV2
|
|
- local: model_doc/cvt
|
|
title: CvT
|
|
- local: model_doc/deformable_detr
|
|
title: Deformable DETR
|
|
- local: model_doc/deit
|
|
title: DeiT
|
|
- local: model_doc/deta
|
|
title: DETA
|
|
- local: model_doc/detr
|
|
title: DETR
|
|
- local: model_doc/dinat
|
|
title: DiNAT
|
|
- local: model_doc/dinov2
|
|
title: DINOV2
|
|
- local: model_doc/dit
|
|
title: DiT
|
|
- local: model_doc/dpt
|
|
title: DPT
|
|
- local: model_doc/efficientformer
|
|
title: EfficientFormer
|
|
- local: model_doc/efficientnet
|
|
title: EfficientNet
|
|
- local: model_doc/focalnet
|
|
title: FocalNet
|
|
- local: model_doc/glpn
|
|
title: GLPN
|
|
- local: model_doc/imagegpt
|
|
title: ImageGPT
|
|
- local: model_doc/levit
|
|
title: LeViT
|
|
- local: model_doc/mask2former
|
|
title: Mask2Former
|
|
- local: model_doc/maskformer
|
|
title: MaskFormer
|
|
- local: model_doc/mobilenet_v1
|
|
title: MobileNetV1
|
|
- local: model_doc/mobilenet_v2
|
|
title: MobileNetV2
|
|
- local: model_doc/mobilevit
|
|
title: MobileViT
|
|
- local: model_doc/mobilevitv2
|
|
title: MobileViTV2
|
|
- local: model_doc/nat
|
|
title: NAT
|
|
- local: model_doc/poolformer
|
|
title: PoolFormer
|
|
- local: model_doc/pvt
|
|
title: Pyramid Vision Transformer (PVT)
|
|
- local: model_doc/regnet
|
|
title: RegNet
|
|
- local: model_doc/resnet
|
|
title: ResNet
|
|
- local: model_doc/segformer
|
|
title: SegFormer
|
|
- local: model_doc/swiftformer
|
|
title: SwiftFormer
|
|
- local: model_doc/swin
|
|
title: Swin Transformer
|
|
- local: model_doc/swinv2
|
|
title: Swin Transformer V2
|
|
- local: model_doc/swin2sr
|
|
title: Swin2SR
|
|
- local: model_doc/table-transformer
|
|
title: Table Transformer
|
|
- local: model_doc/timesformer
|
|
title: TimeSformer
|
|
- local: model_doc/upernet
|
|
title: UperNet
|
|
- local: model_doc/van
|
|
title: VAN
|
|
- local: model_doc/videomae
|
|
title: VideoMAE
|
|
- local: model_doc/vit
|
|
title: Vision Transformer (ViT)
|
|
- local: model_doc/vit_hybrid
|
|
title: ViT Hybrid
|
|
- local: model_doc/vitdet
|
|
title: ViTDet
|
|
- local: model_doc/vit_mae
|
|
title: ViTMAE
|
|
- local: model_doc/vitmatte
|
|
title: ViTMatte
|
|
- local: model_doc/vit_msn
|
|
title: ViTMSN
|
|
- local: model_doc/vivit
|
|
title: ViViT
|
|
- local: model_doc/yolos
|
|
title: YOLOS
|
|
title: Vision models
|
|
- isExpanded: false
|
|
sections:
|
|
- local: model_doc/audio-spectrogram-transformer
|
|
title: Audio Spectrogram Transformer
|
|
- local: model_doc/bark
|
|
title: Bark
|
|
- local: model_doc/clap
|
|
title: CLAP
|
|
- local: model_doc/encodec
|
|
title: EnCodec
|
|
- local: model_doc/hubert
|
|
title: Hubert
|
|
- local: model_doc/mctct
|
|
title: MCTCT
|
|
- local: model_doc/mms
|
|
title: MMS
|
|
- local: model_doc/musicgen
|
|
title: MusicGen
|
|
- local: model_doc/pop2piano
|
|
title: Pop2Piano
|
|
- local: model_doc/seamless_m4t
|
|
title: Seamless-M4T
|
|
- local: model_doc/sew
|
|
title: SEW
|
|
- local: model_doc/sew-d
|
|
title: SEW-D
|
|
- local: model_doc/speech_to_text
|
|
title: Speech2Text
|
|
- local: model_doc/speech_to_text_2
|
|
title: Speech2Text2
|
|
- local: model_doc/speecht5
|
|
title: SpeechT5
|
|
- local: model_doc/unispeech
|
|
title: UniSpeech
|
|
- local: model_doc/unispeech-sat
|
|
title: UniSpeech-SAT
|
|
- local: model_doc/univnet
|
|
title: UnivNet
|
|
- local: model_doc/vits
|
|
title: VITS
|
|
- local: model_doc/wav2vec2
|
|
title: Wav2Vec2
|
|
- local: model_doc/wav2vec2-conformer
|
|
title: Wav2Vec2-Conformer
|
|
- local: model_doc/wav2vec2_phoneme
|
|
title: Wav2Vec2Phoneme
|
|
- local: model_doc/wavlm
|
|
title: WavLM
|
|
- local: model_doc/whisper
|
|
title: Whisper
|
|
- local: model_doc/xls_r
|
|
title: XLS-R
|
|
- local: model_doc/xlsr_wav2vec2
|
|
title: XLSR-Wav2Vec2
|
|
title: Audio models
|
|
- isExpanded: false
|
|
sections:
|
|
- local: model_doc/align
|
|
title: ALIGN
|
|
- local: model_doc/altclip
|
|
title: AltCLIP
|
|
- local: model_doc/blip
|
|
title: BLIP
|
|
- local: model_doc/blip-2
|
|
title: BLIP-2
|
|
- local: model_doc/bridgetower
|
|
title: BridgeTower
|
|
- local: model_doc/bros
|
|
title: BROS
|
|
- local: model_doc/chinese_clip
|
|
title: Chinese-CLIP
|
|
- local: model_doc/clip
|
|
title: CLIP
|
|
- local: model_doc/clipseg
|
|
title: CLIPSeg
|
|
- local: model_doc/clvp
|
|
title: CLVP
|
|
- local: model_doc/data2vec
|
|
title: Data2Vec
|
|
- local: model_doc/deplot
|
|
title: DePlot
|
|
- local: model_doc/donut
|
|
title: Donut
|
|
- local: model_doc/flava
|
|
title: FLAVA
|
|
- local: model_doc/git
|
|
title: GIT
|
|
- local: model_doc/groupvit
|
|
title: GroupViT
|
|
- local: model_doc/idefics
|
|
title: IDEFICS
|
|
- local: model_doc/instructblip
|
|
title: InstructBLIP
|
|
- local: model_doc/kosmos-2
|
|
title: KOSMOS-2
|
|
- local: model_doc/layoutlm
|
|
title: LayoutLM
|
|
- local: model_doc/layoutlmv2
|
|
title: LayoutLMV2
|
|
- local: model_doc/layoutlmv3
|
|
title: LayoutLMV3
|
|
- local: model_doc/layoutxlm
|
|
title: LayoutXLM
|
|
- local: model_doc/lilt
|
|
title: LiLT
|
|
- local: model_doc/lxmert
|
|
title: LXMERT
|
|
- local: model_doc/matcha
|
|
title: MatCha
|
|
- local: model_doc/mgp-str
|
|
title: MGP-STR
|
|
- local: model_doc/nougat
|
|
title: Nougat
|
|
- local: model_doc/oneformer
|
|
title: OneFormer
|
|
- local: model_doc/owlvit
|
|
title: OWL-ViT
|
|
- local: model_doc/owlv2
|
|
title: OWLv2
|
|
- local: model_doc/perceiver
|
|
title: Perceiver
|
|
- local: model_doc/pix2struct
|
|
title: Pix2Struct
|
|
- local: model_doc/sam
|
|
title: Segment Anything
|
|
- local: model_doc/speech-encoder-decoder
|
|
title: Speech Encoder Decoder Models
|
|
- local: model_doc/tapas
|
|
title: TAPAS
|
|
- local: model_doc/trocr
|
|
title: TrOCR
|
|
- local: model_doc/tvlt
|
|
title: TVLT
|
|
- local: model_doc/tvp
|
|
title: TVP
|
|
- local: model_doc/vilt
|
|
title: ViLT
|
|
- local: model_doc/vision-encoder-decoder
|
|
title: Vision Encoder Decoder Models
|
|
- local: model_doc/vision-text-dual-encoder
|
|
title: Vision Text Dual Encoder
|
|
- local: model_doc/visual_bert
|
|
title: VisualBERT
|
|
- local: model_doc/xclip
|
|
title: X-CLIP
|
|
title: Multimodal models
|
|
- isExpanded: false
|
|
sections:
|
|
- local: model_doc/decision_transformer
|
|
title: Decision Transformer
|
|
- local: model_doc/trajectory_transformer
|
|
title: Trajectory Transformer
|
|
title: Reinforcement learning models
|
|
- isExpanded: false
|
|
sections:
|
|
- local: model_doc/autoformer
|
|
title: Autoformer
|
|
- local: model_doc/informer
|
|
title: Informer
|
|
- local: model_doc/patchtst
|
|
title: PatchTST
|
|
- local: model_doc/time_series_transformer
|
|
title: Time Series Transformer
|
|
title: Time series models
|
|
- isExpanded: false
|
|
sections:
|
|
- local: model_doc/graphormer
|
|
title: Graphormer
|
|
title: Graph models
|
|
title: Models
|
|
- sections:
|
|
- local: internal/modeling_utils
|
|
title: Custom Layers and Utilities
|
|
- local: internal/pipelines_utils
|
|
title: Utilities for pipelines
|
|
- local: internal/tokenization_utils
|
|
title: Utilities for Tokenizers
|
|
- local: internal/trainer_utils
|
|
title: Utilities for Trainer
|
|
- local: internal/generation_utils
|
|
title: Utilities for Generation
|
|
- local: internal/image_processing_utils
|
|
title: Utilities for Image Processors
|
|
- local: internal/audio_utils
|
|
title: Utilities for Audio processing
|
|
- local: internal/file_utils
|
|
title: General Utilities
|
|
- local: internal/time_series_utils
|
|
title: Utilities for Time Series
|
|
title: Internal Helpers
|
|
title: API
|