Hugging Face's logo

Transformers documentation

pipelines的工具

Hugging Face's logo
Join the Hugging Face community

and get access to the augmented documentation experience

to get started

pipelines的工具

此页面列出了库为pipelines提供的所有实用程序功能。

其中大多数只有在您研究库中模型的代码时才有用。

参数处理

class transformers.pipelines.ArgumentHandler

< >

( )

Base interface for handling arguments for each Pipeline.

class transformers.pipelines.ZeroShotClassificationArgumentHandler

< >

( )

Handles arguments for zero-shot for text classification by turning each possible label into an NLI premise/hypothesis pair.

class transformers.pipelines.QuestionAnsweringArgumentHandler

< >

( )

QuestionAnsweringPipeline requires the user to provide multiple arguments (i.e. question & context) to be mapped to internal SquadExample.

QuestionAnsweringArgumentHandler manages all the possible to create a SquadExample from the command-line supplied arguments.

数据格式

class transformers.PipelineDataFormat

< >

( output_path: Optional input_path: Optional column: Optional overwrite: bool = False )

Parameters

  • output_path (str) — Where to save the outgoing data.
  • input_path (str) — Where to look for the input data.
  • column (str) — The column to read.
  • overwrite (bool, optional, defaults to False) — Whether or not to overwrite the output_path.

Base class for all the pipeline supported data format both for reading and writing. Supported data formats currently includes:

  • JSON
  • CSV
  • stdin/stdout (pipe)

PipelineDataFormat also includes some utilities to work with multi-columns like mapping from datasets columns to pipelines keyword arguments through the dataset_kwarg_1=dataset_column_1 format.

from_str

< >

( format: str output_path: Optional input_path: Optional column: Optional overwrite = False ) → PipelineDataFormat

Parameters

  • format (str) — The format of the desired pipeline. Acceptable values are "json", "csv" or "pipe".
  • output_path (str, optional) — Where to save the outgoing data.
  • input_path (str, optional) — Where to look for the input data.
  • column (str, optional) — The column to read.
  • overwrite (bool, optional, defaults to False) — Whether or not to overwrite the output_path.

Returns

PipelineDataFormat

The proper data format.

Creates an instance of the right subclass of PipelineDataFormat depending on format.

save

< >

( data: Union )

Parameters

  • data (dict or list of dict) — The data to store.

Save the provided data object with the representation for the current PipelineDataFormat.

save_binary

< >

( data: Union ) → str

Parameters

  • data (dict or list of dict) — The data to store.

Returns

str

Path where the data has been saved.

Save the provided data object as a pickle-formatted binary data on the disk.

class transformers.CsvPipelineDataFormat

< >

( output_path: Optional input_path: Optional column: Optional overwrite = False )

Parameters

  • output_path (str) — Where to save the outgoing data.
  • input_path (str) — Where to look for the input data.
  • column (str) — The column to read.
  • overwrite (bool, optional, defaults to False) — Whether or not to overwrite the output_path.

Support for pipelines using CSV data format.

save

< >

( data: List )

Parameters

  • data (List[dict]) — The data to store.

Save the provided data object with the representation for the current PipelineDataFormat.

class transformers.JsonPipelineDataFormat

< >

( output_path: Optional input_path: Optional column: Optional overwrite = False )

Parameters

  • output_path (str) — Where to save the outgoing data.
  • input_path (str) — Where to look for the input data.
  • column (str) — The column to read.
  • overwrite (bool, optional, defaults to False) — Whether or not to overwrite the output_path.

Support for pipelines using JSON file format.

save

< >

( data: dict )

Parameters

  • data (dict) — The data to store.

Save the provided data object in a json file.

class transformers.PipedPipelineDataFormat

< >

( output_path: Optional input_path: Optional column: Optional overwrite: bool = False )

Parameters

  • output_path (str) — Where to save the outgoing data.
  • input_path (str) — Where to look for the input data.
  • column (str) — The column to read.
  • overwrite (bool, optional, defaults to False) — Whether or not to overwrite the output_path.

Read data from piped input to the python process. For multi columns data, columns should separated by

If columns are provided, then the output will be a dictionary with {column_x: value_x}

save

< >

( data: dict )

Parameters

  • data (dict) — The data to store.

Print the data.

实用函数

class transformers.pipelines.PipelineException

< >

( task: str model: str reason: str )

Parameters

  • task (str) — The task of the pipeline.
  • model (str) — The model used by the pipeline.
  • reason (str) — The error message to display.

Raised by a Pipeline when handling call.

< > Update on GitHub

←自定义层和工具 Tokenizers工具→