Packages

class SummarizationModel extends Model[SummarizationModel] with RawAnnotator[SummarizationModel] with CanBeLazy with SummarizationParams

Fitted model produced by Summarization.

Orchestrates the resolved summarization delegate at the DataFrame level: prompt building, long-document chunking (hierarchical map/reduce summarization), delegate inference, output cleanup and transparency metadata. The delegate is one of:

  • AutoGGUFModel for method llm,
  • BartTransformer for method encoder_decoder,
  • MPNetEmbeddings (+ rule-based sentence detection and a PacSum-style ranker) for method extractive.

Saving this model persists the delegate (model weights included) under the model path, so fitted pipelines reload without network access.

Notes:

  • The summarization method is bound at fit time: this model only holds the delegate of the method it was fitted with. Changing method on a fitted model fails at transform with an explanatory error; fit a new Summarization stage instead. All other task parameters (lengths, style, focus, strategy, ...) can be changed freely after fit.
  • As a DataFrame-level orchestrator this annotator is not supported in LightPipeline.
  • transform configures the shared delegate (input/output columns, generation settings) in place, so a single model instance is not safe for concurrent transform calls; use one instance per concurrent caller.
  • Transforms cache the input row ids and the computed summaries for the lifetime of the returned DataFrame (generative inference intermediates are released eagerly). These caches back the returned DataFrame and cannot be unpersisted through this API; they are freed when the SparkSession ends or via spark.catalog.clearCache() (which clears all cached data). The encoder_decoder method pins inference to a single partition (the BART backend is not thread-safe); the llm and extractive methods keep the input partitioning.
  • For the llm method the document text is embedded into the prompt, so a document containing instructions can influence its own summary (prompt injection); the system prompt reduces but does not eliminate this.
Linear Supertypes
SummarizationParams, CanBeLazy, RawAnnotator[SummarizationModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[SummarizationModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SummarizationModel
  2. SummarizationParams
  3. CanBeLazy
  4. RawAnnotator
  5. HasOutputAnnotationCol
  6. HasInputAnnotationCols
  7. HasOutputAnnotatorType
  8. ParamsAndFeaturesWritable
  9. HasFeatures
  10. DefaultParamsWritable
  11. MLWritable
  12. Model
  13. Transformer
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SummarizationModel()
  2. new SummarizationModel(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. 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. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  10. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  11. val chunkOverlap: IntParam

    Number of sentences repeated between consecutive chunks (Default: 1).

    Number of sentences repeated between consecutive chunks (Default: 1).

    Definition Classes
    SummarizationParams
  12. val chunkSize: IntParam

    Chunk size in approximate tokens used for hierarchical summarization (Default: 0 = derive automatically from the model's context limit).

    Chunk size in approximate tokens used for hierarchical summarization (Default: 0 = derive automatically from the model's context limit).

    Definition Classes
    SummarizationParams
  13. final def clear(param: Param[_]): SummarizationModel.this.type
    Definition Classes
    Params
  14. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  15. def close(): Unit

    Closes the llama.cpp backend if the llm delegate is loaded, freeing native resources.

  16. def copy(extra: ParamMap): SummarizationModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    SummarizationModel → RawAnnotator → Model → Transformer → PipelineStage → Params
  17. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  18. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  19. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  21. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  22. def explainParams(): String
    Definition Classes
    Params
  23. final val extraInputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  24. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    SummarizationModel → RawAnnotator
  25. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  26. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  27. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  28. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  29. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  30. val focus: Param[String]

    Optional free-text focus hint included in the LLM prompt, e.g.

    Optional free-text focus hint included in the LLM prompt, e.g. "main findings" (Default: ""). Only applies to the llm method.

    Definition Classes
    SummarizationParams
  31. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  32. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  33. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  34. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  35. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  36. def getChunkOverlap: Int

    Definition Classes
    SummarizationParams
  37. def getChunkSize: Int

    Definition Classes
    SummarizationParams
  38. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  39. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  40. def getEmbeddingsDelegate: MPNetEmbeddings

  41. def getFocus: String

    Definition Classes
    SummarizationParams
  42. def getGpuLayers: Int

    Definition Classes
    SummarizationParams
  43. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  44. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  45. def getLlmDelegate: AutoGGUFModel

  46. def getLongDocumentStrategy: String

    Definition Classes
    SummarizationParams
  47. def getMaxSummaryLength: Int

    Definition Classes
    SummarizationParams
  48. def getMethod: String

    Definition Classes
    SummarizationParams
  49. def getMinSummaryLength: Int

    Definition Classes
    SummarizationParams
  50. def getMmrLambda: Float

    Definition Classes
    SummarizationParams
  51. def getModel: String

    Definition Classes
    SummarizationParams
  52. def getNoRepeatNgramSize: Int

    Definition Classes
    SummarizationParams
  53. def getNumBeams: Int

    Definition Classes
    SummarizationParams
  54. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  55. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  56. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  57. def getPositionBias: Float

    Definition Classes
    SummarizationParams
  58. def getResolvedModel: String

  59. def getSeq2SeqDelegate: BartTransformer

  60. def getSummaryStyle: String

    Definition Classes
    SummarizationParams
  61. def getTemperature: Float

    Definition Classes
    SummarizationParams
  62. def getTopP: Float

    Definition Classes
    SummarizationParams
  63. val gpuLayers: IntParam

    Number of model layers offloaded to the GPU for the llm method (Default: 99 = offload all).

    Number of model layers offloaded to the GPU for the llm method (Default: 99 = offload all). Set to 0 on CPU-only clusters. Ignored by the other methods.

    Definition Classes
    SummarizationParams
  64. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  65. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  66. def hasParent: Boolean
    Definition Classes
    Model
  67. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  68. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  69. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. val inputAnnotatorTypes: Array[String]

    Input Annotator Type: DOCUMENT

    Input Annotator Type: DOCUMENT

    Definition Classes
    SummarizationModel → HasInputAnnotationCols
  71. final val inputCols: StringArrayParam

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  72. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  73. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  74. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  75. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  76. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  77. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  78. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  85. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  88. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  89. val longDocumentStrategy: Param[String]

    Strategy for documents longer than the model context: auto, truncate or hierarchical (Default: auto).

    Strategy for documents longer than the model context: auto, truncate or hierarchical (Default: auto). auto summarizes directly when the document fits and falls back to hierarchical chunk-then-combine summarization when it does not. Since hierarchical also summarizes a fitting document in a single pass, auto and hierarchical currently behave identically; only truncate differs (it cuts the document to the context budget).

    Definition Classes
    SummarizationParams
  90. val maxSummaryLength: IntParam

    Target maximum summary length in words/tokens, approximate (Default: 250).

    Target maximum summary length in words/tokens, approximate (Default: 250).

    Definition Classes
    SummarizationParams
  91. val method: Param[String]

    Summarization method: llm, encoder_decoder or extractive (Default: llm).

    Summarization method: llm, encoder_decoder or extractive (Default: llm).

    • llm: an instruction-tuned GGUF LLM (via AutoGGUFModel / llama.cpp) prompted for summarization.
    • encoder_decoder: a specialized abstractive summarization model (DistilBART).
    • extractive: selects the most central sentences of the original document (embedding-based centrality with position prior and MMR redundancy control).
    Definition Classes
    SummarizationParams
  92. val minSummaryLength: IntParam

    Minimum summary length in words/tokens, generative methods only (Default: 20).

    Minimum summary length in words/tokens, generative methods only (Default: 20).

    Definition Classes
    SummarizationParams
  93. val mmrLambda: FloatParam

    MMR trade-off between relevance and redundancy in extractive selection, higher = more relevance-driven (Default: 0.7).

    MMR trade-off between relevance and redundancy in extractive selection, higher = more relevance-driven (Default: 0.7). Only applies to the extractive method.

    Definition Classes
    SummarizationParams
  94. val model: Param[String]

    Optional pretrained model name overriding the method's default model (Default: "" = use the method's default).

    Optional pretrained model name overriding the method's default model (Default: "" = use the method's default).

    Definition Classes
    SummarizationParams
  95. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  96. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  97. val noRepeatNgramSize: IntParam

    Size of n-grams that may not repeat in the generated summary (Default: 3).

    Size of n-grams that may not repeat in the generated summary (Default: 3). Only applies to the encoder_decoder method; 0 disables the constraint.

    Definition Classes
    SummarizationParams
  98. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  99. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  100. val numBeams: IntParam

    Number of beams for beam search (Default: 4).

    Number of beams for beam search (Default: 4). Only applies to the encoder_decoder method.

    Definition Classes
    SummarizationParams
  101. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    SummarizationModel → ParamsAndFeaturesWritable
  102. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  103. val outputAnnotatorType: String

    Output Annotator Type: DOCUMENT

    Output Annotator Type: DOCUMENT

    Definition Classes
    SummarizationModel → HasOutputAnnotatorType
  104. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  105. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  106. var parent: Estimator[SummarizationModel]
    Definition Classes
    Model
  107. val positionBias: FloatParam

    Weight of the lead-position prior in extractive sentence ranking (Default: 0.3).

    Weight of the lead-position prior in extractive sentence ranking (Default: 0.3). Only applies to the extractive method.

    Definition Classes
    SummarizationParams
  108. val resolvedModel: Param[String]

    Name of the pretrained model resolved at fit time (for transparency metadata).

  109. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  110. def set[T](feature: StructFeature[T], value: T): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  111. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  112. def set[T](feature: SetFeature[T], value: Set[T]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  113. def set[T](feature: ArrayFeature[T], value: Array[T]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  114. final def set(paramPair: ParamPair[_]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  115. final def set(param: String, value: Any): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  116. final def set[T](param: Param[T], value: T): SummarizationModel.this.type
    Definition Classes
    Params
  117. def setChunkOverlap(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  118. def setChunkSize(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  119. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  120. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  121. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  122. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  123. final def setDefault(paramPairs: ParamPair[_]*): SummarizationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  124. final def setDefault[T](param: Param[T], value: T): SummarizationModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  125. def setEmbeddingsDelegate(value: MPNetEmbeddings): SummarizationModel.this.type

  126. def setExtraInputCols(value: Array[String]): SummarizationModel.this.type
    Definition Classes
    HasInputAnnotationCols
  127. def setFocus(value: String): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  128. def setGpuLayers(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  129. final def setInputCols(value: String*): SummarizationModel.this.type
    Definition Classes
    HasInputAnnotationCols
  130. def setInputCols(value: Array[String]): SummarizationModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  131. def setLazyAnnotator(value: Boolean): SummarizationModel.this.type
    Definition Classes
    CanBeLazy
  132. def setLlmDelegate(value: AutoGGUFModel): SummarizationModel.this.type

  133. def setLongDocumentStrategy(value: String): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  134. def setMaxSummaryLength(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  135. def setMethod(value: String): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  136. def setMinSummaryLength(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  137. def setMmrLambda(value: Float): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  138. def setModel(value: String): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  139. def setNoRepeatNgramSize(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  140. def setNumBeams(value: Int): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  141. final def setOutputCol(value: String): SummarizationModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  142. def setParent(parent: Estimator[SummarizationModel]): SummarizationModel
    Definition Classes
    Model
  143. def setPositionBias(value: Float): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  144. def setResolvedModel(value: String): SummarizationModel.this.type

  145. def setSeq2SeqDelegate(value: BartTransformer): SummarizationModel.this.type

  146. def setSummaryStyle(value: String): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  147. def setTemperature(value: Float): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  148. def setTopP(value: Float): SummarizationModel.this.type

    Definition Classes
    SummarizationParams
  149. val summaryStyle: Param[String]

    Summary style used to build the LLM prompt: concise, detailed or bullets (Default: concise).

    Summary style used to build the LLM prompt: concise, detailed or bullets (Default: concise). Only applies to the llm method.

    Definition Classes
    SummarizationParams
  150. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  151. val temperature: FloatParam

    Generation temperature (Default: 0.2).

    Generation temperature (Default: 0.2). Applies to the llm method.

    Definition Classes
    SummarizationParams
  152. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  153. val topP: FloatParam

    Top-p (nucleus) sampling (Default: 0.9).

    Top-p (nucleus) sampling (Default: 0.9). Applies to the llm method.

    Definition Classes
    SummarizationParams
  154. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    SummarizationModel → Transformer
  155. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  156. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  157. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    RawAnnotator → PipelineStage
  158. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  159. val uid: String
    Definition Classes
    SummarizationModel → Identifiable
  160. def validate(schema: StructType): Boolean

    takes a Dataset and checks to see if all the required annotation types are present.

    takes a Dataset and checks to see if all the required annotation types are present.

    schema

    to be validated

    returns

    True if all the required types are present, else false

    Attributes
    protected
    Definition Classes
    RawAnnotator
  161. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  162. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  163. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  164. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  165. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from SummarizationParams

Inherited from CanBeLazy

Inherited from RawAnnotator[SummarizationModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[SummarizationModel]

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

Parameters

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters