TransformersTokenClassifier
NER task
Subclass of NERTask.
Module: implementation.tasks
Default predictor
This task uses TransformersModel by default with this configuration:
See:
Methods and properties
Main methods and properties
__init__
Arguments:
predictor (Predictor[Any, Any], optional): Predictor that will be used in task. If equals to None, default predictor will be used. Defaults to None.
preprocess (Optional[Component], optional): Component executed before predictor. Defaults to None.
postprocess (Optional[Component], optional): Component executed after predictor. If equals to None, default component will be used. Defaults to None. Default component: TokenClassifierPostprocessor
input_class (Type[Input], optional): Class for input validation. Defaults to TransformersBasicInput.
output_class (Type[Output], optional): Class for output validation. Defaults to TransformersTokenClassifierOutput.
name (Optional[str], optional): Name for identification. If equals to None, class name will be used. Defaults to None.
TransformersTokenClassifierOutput
Subclass of NEROutput. Type of NEROutput[ClassifiedEntity].
TokenClassifierPostprocessor
Format model output. Subclass of Action. Type of Action[Dict[str, Any], Dict[str, Any]].
__init__
Arguments:
threshold (float): Entities threshold score. Defaults to 0.
name (Optional[str], optional): Name for identification. If equals to None, class name will be used. Defaults to None.
execute
Arguments:
input_data (Dict[str, Any]): Expected keys:
"output" (List[Dict[str, Any]]): Model output;
Returns:
Dict[str, Any]: Expected keys:
"output" (List[ClassifiedEntity]): Classified entities;
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