nlp_assertion_logreg_pretrained: Load a pretrained Spark NLP Assertion LogReg model

In r-spark/sparknlp: R Interface to John Snow Labs Spark NLP

Load a pretrained Spark NLP Assertion LogReg model

Description

Create a pretrained Spark NLP AssertionLogRegModel model

Usage

nlp_assertion_logreg_pretrained(
  sc,
  input_cols,
  output_col,
  before = NULL,
  after = NULL,
  start_col = NULL,
  end_col = NULL,
  lazy_annotator = NULL,
  storage_ref = NULL,
  name = NULL,
  lang = NULL,
  remote_loc = NULL
)

Arguments

sc	A Spark connection
input_cols	Input columns. String array.
output_col	Output column. String.
before	Amount of tokens from the context before the target
after	Amount of tokens from the context after the target
start_col	Column that contains the token number for the start of the target
end_col	Column that contains the token number for the end of the target
lazy_annotator	a Param in Annotators that allows them to stand idle in the Pipeline and do nothing. Can be called by other Annotators in a RecursivePipeline
storage_ref	storage reference for embeddings
name	the name of the model to load. If NULL will use the default value
lang	the language of the model to be loaded. If NULL will use the default value
remote_loc	the remote location of the model. If NULL will use the default value

Value

The Spark NLP model with the pretrained model loaded

r-spark/sparknlp documentation built on Oct. 15, 2022, 10:50 a.m.