Unverified Commit e4920c92 authored by Sylvain Gugger's avatar Sylvain Gugger Committed by GitHub
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Doc pipelines (#6175)



* Init work on pipelines doc

* Work in progress

* Work in progress

* Doc pipelines

* Rm unwanted default

* Apply suggestions from code review

Lysandre comments
Co-authored-by: default avatarLysandre Debut <lysandre@huggingface.co>
Co-authored-by: default avatarLysandre Debut <lysandre@huggingface.co>
parent b6b2f227
......@@ -207,3 +207,4 @@ conversion utilities for the following models:
model_doc/dpr
internal/modeling_utils
internal/tokenization_utils
internal/pipelines_utils
\ No newline at end of file
Utilities for pipelines
-----------------------
This page lists all the utility functions the library provides for pipelines.
Most of those are only useful if you are studying the code of the models in the library.
Argument handling
~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.pipelines.ArgumentHandler
.. autoclass:: transformers.pipelines.ZeroShotClassificationArgumentHandler
.. autoclass:: transformers.pipelines.QuestionAnsweringArgumentHandler
Data format
~~~~~~~~~~~
.. autoclass:: transformers.pipelines.PipelineDataFormat
:members:
.. autoclass:: transformers.pipelines.CsvPipelineDataFormat
:members:
.. autoclass:: transformers.pipelines.JsonPipelineDataFormat
:members:
.. autoclass:: transformers.pipelines.PipedPipelineDataFormat
:members:
Utilities
~~~~~~~~~
.. autofunction:: transformers.pipelines.get_framework
.. autoclass:: transformers.pipelines.PipelineException
......@@ -41,3 +41,9 @@ The other methods that are common to each model are defined in :class:`~transfor
.. autoclass:: transformers.modeling_tf_utils.TFModelUtilsMixin
:members:
Generative models
~~~~~~~~~~~~~~~~~
Coming soon
......@@ -3,13 +3,23 @@ Pipelines
The pipelines are a great and easy way to use models for inference. These pipelines are objects that abstract most
of the complex code from the library, offering a simple API dedicated to several tasks, including Named Entity
Recognition, Masked Language Modeling, Sentiment Analysis, Feature Extraction and Question Answering.
Recognition, Masked Language Modeling, Sentiment Analysis, Feature Extraction and Question Answering. See the
:doc:`task summary <../task_summary>` for examples of use.
There are two categories of pipeline abstractions to be aware about:
- The :func:`~transformers.pipeline` which is the most powerful object encapsulating all other pipelines
- The other task-specific pipelines, such as :class:`~transformers.TokenClassificationPipeline`
or :class:`~transformers.QuestionAnsweringPipeline`
- The :func:`~transformers.pipeline` which is the most powerful object encapsulating all other pipelines.
- The other task-specific pipelines:
- :class:`~transformers.ConversationalPipeline`
- :class:`~transformers.FeatureExtractionPipeline`
- :class:`~transformers.FillMaskPipeline`
- :class:`~transformers.QuestionAnsweringPipeline`
- :class:`~transformers.SummarizationPipeline`
- :class:`~transformers.TextClassificationPipeline`
- :class:`~transformers.TextGenerationPipeline`
- :class:`~transformers.TokenClassificationPipeline`
- :class:`~transformers.TranslationPipeline`
The pipeline abstraction
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
......@@ -21,61 +31,75 @@ other pipeline but requires an additional argument which is the `task`.
The task specific pipelines
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Parent class: Pipeline
=========================================
.. autoclass:: transformers.Pipeline
:members: predict, transform, save_pretrained
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TokenClassificationPipeline
ConversationalPipeline
==========================================
.. autoclass:: transformers.TokenClassificationPipeline
.. autoclass:: transformers.Conversation
NerPipeline
.. autoclass:: transformers.ConversationalPipeline
:special-members: __call__
:members:
FeatureExtractionPipeline
==========================================
This class is an alias of the :class:`~transformers.TokenClassificationPipeline` defined above. Please refer to that pipeline for
documentation and usage examples.
.. autoclass:: transformers.FeatureExtractionPipeline
:special-members: __call__
:members:
FillMaskPipeline
==========================================
.. autoclass:: transformers.FillMaskPipeline
:special-members: __call__
:members:
FeatureExtractionPipeline
==========================================
.. autoclass:: transformers.FeatureExtractionPipeline
TextClassificationPipeline
NerPipeline
==========================================
.. autoclass:: transformers.TextClassificationPipeline
This class is an alias of the :class:`~transformers.TokenClassificationPipeline` defined below. Please refer to that
pipeline for documentation and usage examples.
QuestionAnsweringPipeline
==========================================
.. autoclass:: transformers.QuestionAnsweringPipeline
:special-members: __call__
:members:
SummarizationPipeline
==========================================
.. autoclass:: transformers.SummarizationPipeline
:special-members: __call__
:members:
TextClassificationPipeline
==========================================
.. autoclass:: transformers.TextClassificationPipeline
:special-members: __call__
:members:
TextGenerationPipeline
==========================================
.. autoclass:: transformers.TextGenerationPipeline
:special-members: __call__
:members:
ConversationalPipeline
TokenClassificationPipeline
==========================================
.. autoclass:: transformers.Conversation
.. autoclass:: transformers.TokenClassificationPipeline
:special-members: __call__
:members:
.. autoclass:: transformers.ConversationalPipeline
\ No newline at end of file
Parent class: :obj:`Pipeline`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.Pipeline
:members:
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