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69 lines
2.1 KiB
ReStructuredText
69 lines
2.1 KiB
ReStructuredText
Pipelines
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----------------------------------------------------
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The pipelines are a great and easy way to use models for inference. These pipelines are objects that abstract most
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of the complex code from the library, offering a simple API dedicated to several tasks, including Named Entity
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Recognition, Masked Language Modeling, Sentiment Analysis, Feature Extraction and Question Answering.
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There are two categories of pipeline abstractions to be aware about:
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- The :class:`~transformers.pipeline` which is the most powerful object encapsulating all other pipelines
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- The other task-specific pipelines, such as :class:`~transformers.NerPipeline`
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or :class:`~transformers.QuestionAnsweringPipeline`
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The pipeline abstraction
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The `pipeline` abstraction is a wrapper around all the other available pipelines. It is instantiated as any
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other pipeline but requires an additional argument which is the `task`.
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.. autoclass:: transformers.pipeline
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:members:
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The task specific pipelines
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Parent class: Pipeline
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=========================================
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.. autoclass:: transformers.Pipeline
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:members: predict, transform, save_pretrained
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NerPipeline
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==========================================
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.. autoclass:: transformers.NerPipeline
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TokenClassificationPipeline
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==========================================
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This class is an alias of the :class:`~transformers.NerPipeline` defined above. Please refer to that pipeline for
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documentation and usage examples.
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FillMaskPipeline
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==========================================
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.. autoclass:: transformers.FillMaskPipeline
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FeatureExtractionPipeline
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==========================================
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.. autoclass:: transformers.FeatureExtractionPipeline
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TextClassificationPipeline
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==========================================
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.. autoclass:: transformers.TextClassificationPipeline
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QuestionAnsweringPipeline
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==========================================
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.. autoclass:: transformers.QuestionAnsweringPipeline
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SummarizationPipeline
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==========================================
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.. autoclass:: transformers.SummarizationPipeline
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