templates.ModelBasedTemplateSchema

class templates.ModelBasedTemplateSchema(*args, **kwargs)

Model Based template

Parameters

Parameters

Name	Type	Default	Info
include_fields	List[str]		The fields to include in the model featurization.
target_field	str		The field containing the model predictions.
model_type	str		The specific model used, must be contained in: [“zsl_text_match”, “zsl_entailment”, “masked_lm”, “logistic_regression”, “one_class_svm”, “tfidf_logreg”, “setfit”, “sdnet”, “sequence_embedding”]
model_name	str		A user specified string name given to the trained model.
value	int		The class index this LF should vote for.
dirpath	str		The path to the stored model in minio.
threshold	float		The confidence threshold below which this LF should abstain.
unique_model_name	Optional[str]	None	A unique name for the model, usually the same as dirpath.
is_multilabel	bool	False	Whether or not the task this LF is being applied to is multi-label.
multilabel_absent_as_abstain	bool	True	If this is a multi-label task, True if we should replace “absent” votes output by the model with “abstain” votes.

artifact\_config\_keys

artifact_config_keys

static artifact_config_keys()

The names of the fields in the template schema pydantic model that represent paths to files or directories that contain data which back the LF template. For example, paths to a dictionary on disk that’s used within an LF.

Return type

Return type

List[str]