class LegalClassifierDLModel extends ClassifierDLModel

MedicalBertForSequenceClassification can load Bert Models with sequence classification/regression head on top (a linear layer on top of the pooled output) e.g. for multi-class document classification tasks.

Pretrained models can be loaded with pretrained of the companion object:

val sequenceClassifier = MedicalBertForSequenceClassification.pretrained()
  .setInputCols("token", "document")
  .setOutputCol("label")

The default model is "bert_sequence_classifier_ade", if no name is provided.

For available pretrained models please see the Models Hub.

Models from the HuggingFace 🤗 Transformers library are also compatible with Spark NLP 🚀. The Spark NLP Workshop example shows how to import them https://github.com/JohnSnowLabs/spark-nlp/discussions/5669.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base._
import com.johnsnowlabs.nlp.annotator._
import org.apache.spark.ml.Pipeline

val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("document")

val tokenizer = new Tokenizer()
  .setInputCols("document")
  .setOutputCol("token")

val sequenceClassifier = MedicalBertForSequenceClassification.pretrained()
  .setInputCols("token", "document")
  .setOutputCol("label")
  .setCaseSensitive(true)

val pipeline = new Pipeline().setStages(Array(
  documentAssembler,
  tokenizer,
  sequenceClassifier
))

val data = Seq("John Lenon was born in London and lived in Paris. My name is Sarah and I live in London").toDF("text")
val result = pipeline.fit(data).transform(data)

result.select("label.result").show(false)
+--------------------+
|result              |
+--------------------+
|[True, False]       |
+--------------------+
See also

MedicalBertForSequenceClassification for sequnece-level classification

Annotators Main Page for a list of transformer based classifiers

Linear Supertypes
ClassifierDLModel, HasEngine, HasStorageRef, WriteTensorflowModel, HasSimpleAnnotate[ClassifierDLModel], AnnotatorModel[ClassifierDLModel], CanBeLazy, RawAnnotator[ClassifierDLModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[ClassifierDLModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
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  2. By Inheritance
Inherited
  1. LegalClassifierDLModel
  2. ClassifierDLModel
  3. HasEngine
  4. HasStorageRef
  5. WriteTensorflowModel
  6. HasSimpleAnnotate
  7. AnnotatorModel
  8. CanBeLazy
  9. RawAnnotator
  10. HasOutputAnnotationCol
  11. HasInputAnnotationCols
  12. HasOutputAnnotatorType
  13. ParamsAndFeaturesWritable
  14. HasFeatures
  15. DefaultParamsWritable
  16. MLWritable
  17. Model
  18. Transformer
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new LegalClassifierDLModel()

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

  2. new LegalClassifierDLModel(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. type AnnotationContent = Seq[Row]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]
    Definition Classes
    LegalClassifierDLModel → ClassifierDLModel → HasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    LegalClassifierDLModel → ClassifierDLModel → AnnotatorModel
  14. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  15. val classes: StringArrayParam
    Definition Classes
    ClassifierDLModel
  16. final def clear(param: Param[_]): LegalClassifierDLModel.this.type
    Definition Classes
    Params
  17. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  18. val configProtoBytes: IntArrayParam
    Definition Classes
    ClassifierDLModel
  19. def copy(extra: ParamMap): ClassifierDLModel
    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  20. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  22. val datasetParams: StructFeature[ClassifierDatasetEncoderParams]
    Definition Classes
    ClassifierDLModel
  23. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  24. def dfAnnotate: UserDefinedFunction
    Definition Classes
    HasSimpleAnnotate
  25. val engine: Param[String]
    Definition Classes
    HasEngine
  26. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  28. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  29. def explainParams(): String
    Definition Classes
    Params
  30. final val extraInputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  31. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  32. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  33. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  34. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  35. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  36. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  37. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  38. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  39. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  40. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  43. def getClasses: Array[String]
    Definition Classes
    ClassifierDLModel
  44. def getConfigProtoBytes: Option[Array[Byte]]
    Definition Classes
    ClassifierDLModel
  45. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  46. def getEngine: String
    Definition Classes
    HasEngine
  47. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  48. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  49. def getModelIfNotSet: TensorflowClassifier
    Definition Classes
    ClassifierDLModel
  50. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  51. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  52. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  53. def getStorageRef: String
    Definition Classes
    HasStorageRef
  54. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  55. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  56. def hasParent: Boolean
    Definition Classes
    Model
  57. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  58. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  59. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. val inputAnnotatorTypes: Array[AnnotatorType]
    Definition Classes
    ClassifierDLModel → HasInputAnnotationCols
  61. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  62. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  63. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  64. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  65. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  66. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  67. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  68. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  75. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  80. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  81. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  82. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  83. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    ClassifierDLModel → ParamsAndFeaturesWritable
  84. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  85. val outputAnnotatorType: String
    Definition Classes
    ClassifierDLModel → HasOutputAnnotatorType
  86. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  87. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  88. var parent: Estimator[ClassifierDLModel]
    Definition Classes
    Model
  89. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  90. def set[T](feature: StructFeature[T], value: T): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  91. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  92. def set[T](feature: SetFeature[T], value: Set[T]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  93. def set[T](feature: ArrayFeature[T], value: Array[T]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  94. final def set(paramPair: ParamPair[_]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  95. final def set(param: String, value: Any): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  96. final def set[T](param: Param[T], value: T): LegalClassifierDLModel.this.type
    Definition Classes
    Params
  97. def setConfigProtoBytes(bytes: Array[Int]): LegalClassifierDLModel.this.type
    Definition Classes
    ClassifierDLModel
  98. def setDatasetParams(params: ClassifierDatasetEncoderParams): LegalClassifierDLModel.this.type
    Definition Classes
    ClassifierDLModel
  99. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  100. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. final def setDefault(paramPairs: ParamPair[_]*): LegalClassifierDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  104. final def setDefault[T](param: Param[T], value: T): LegalClassifierDLModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  105. def setExtraInputCols(value: Array[String]): LegalClassifierDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  106. final def setInputCols(value: String*): LegalClassifierDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  107. def setInputCols(value: Array[String]): LegalClassifierDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  108. def setLazyAnnotator(value: Boolean): LegalClassifierDLModel.this.type
    Definition Classes
    CanBeLazy
  109. def setModelIfNotSet(spark: SparkSession, tf: TensorflowWrapper): LegalClassifierDLModel.this.type
    Definition Classes
    ClassifierDLModel
  110. final def setOutputCol(value: String): LegalClassifierDLModel.this.type
    Definition Classes
    HasOutputAnnotationCol
  111. def setParent(parent: Estimator[ClassifierDLModel]): ClassifierDLModel
    Definition Classes
    Model
  112. def setStorageRef(value: String): LegalClassifierDLModel.this.type
    Definition Classes
    HasStorageRef
  113. val storageRef: Param[String]
    Definition Classes
    HasStorageRef
  114. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  115. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  116. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  117. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  118. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  119. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  120. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  121. val uid: String
    Definition Classes
    LegalClassifierDLModel → ClassifierDLModel → Identifiable
  122. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  123. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  124. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  125. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  126. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  127. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  128. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  129. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  130. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  131. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from ClassifierDLModel

Inherited from HasEngine

Inherited from HasStorageRef

Inherited from WriteTensorflowModel

Inherited from HasSimpleAnnotate[ClassifierDLModel]

Inherited from AnnotatorModel[ClassifierDLModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[ClassifierDLModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[ClassifierDLModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Members