class MedicalTextGenerator extends AnnotatorModel[MedicalQuestionAnswering] with GPTGenerationParams with HasCaseSensitiveProperties with HasBatchedAnnotate[MedicalQuestionAnswering] with ParamsAndFeaturesWritable with WriteTensorflowModel with WriteOnnxModel with WriteSentencePieceModel with HasEngine with CheckLicense

Linear Supertypes
CheckLicense, HasEngine, WriteSentencePieceModel, WriteOnnxModel, WriteTensorflowModel, HasBatchedAnnotate[MedicalQuestionAnswering], HasCaseSensitiveProperties, GPTGenerationParams, AnnotatorModel[MedicalQuestionAnswering], CanBeLazy, RawAnnotator[MedicalQuestionAnswering], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[MedicalQuestionAnswering], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
FinanceQuestionAnswering, FinanceTextGenerator, LegalQuestionAnswering, LegalTextGenerator, MedicalQuestionAnswering, Text2SQL
Ordering
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  3. By Inheritance
Inherited
  1. MedicalTextGenerator
  2. CheckLicense
  3. HasEngine
  4. WriteSentencePieceModel
  5. WriteOnnxModel
  6. WriteTensorflowModel
  7. HasBatchedAnnotate
  8. HasCaseSensitiveProperties
  9. GPTGenerationParams
  10. AnnotatorModel
  11. CanBeLazy
  12. RawAnnotator
  13. HasOutputAnnotationCol
  14. HasInputAnnotationCols
  15. HasOutputAnnotatorType
  16. ParamsAndFeaturesWritable
  17. HasFeatures
  18. DefaultParamsWritable
  19. MLWritable
  20. Model
  21. Transformer
  22. PipelineStage
  23. Logging
  24. Params
  25. Serializable
  26. Serializable
  27. Identifiable
  28. AnyRef
  29. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

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. val DOCUMENT_VARIABLE_NAME: String
    Attributes
    protected
  10. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. val additionalTokens: MapFeature[Int, String]

    Additional tokens

  12. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  13. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  14. def batchAnnotate(batchedAnnotations: Seq[Array[Annotation]]): Seq[Seq[Annotation]]

    takes a document and annotations and produces new annotations of this annotator's annotation type

    takes a document and annotations and produces new annotations of this annotator's annotation type

    batchedAnnotations

    Annotations that correspond to inputAnnotationCols generated by previous annotators if any

    returns

    any number of annotations processed for every input annotation. Not necessary one to one relationship

    Definition Classes
    MedicalTextGenerator → HasBatchedAnnotate
  15. def batchProcess(rows: Iterator[_]): Iterator[Row]
    Definition Classes
    HasBatchedAnnotate
  16. val batchSize: IntParam
    Definition Classes
    HasBatchedAnnotate
  17. def batchedAnnotateWithoutPromptTemplate(batchedAnnotations: Seq[Array[Annotation]]): Seq[Seq[Annotation]]
  18. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  19. val caseSensitive: BooleanParam
    Definition Classes
    HasCaseSensitiveProperties
  20. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  21. def checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
    Definition Classes
    CheckLicense
  22. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  23. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  24. def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  25. final def clear(param: Param[_]): MedicalTextGenerator.this.type
    Definition Classes
    Params
  26. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  27. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  28. def copy(extra: ParamMap): MedicalQuestionAnswering
    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  29. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  30. val customPrompt: Param[String]

    Custom model prompt

  31. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  32. val doSample: BooleanParam

    Whether or not to use sampling, use greedy decoding otherwise (Default: false)

    Whether or not to use sampling, use greedy decoding otherwise (Default: false)

    Definition Classes
    GPTGenerationParams
  33. val engine: Param[String]
    Definition Classes
    HasEngine
  34. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  35. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  36. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  37. def explainParams(): String
    Definition Classes
    Params
  38. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  39. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  40. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  41. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  42. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  43. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  44. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  45. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  46. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  47. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  48. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  49. def getAdditionalTokens: Map[Int, String]

    Get additional tokens

  50. def getAdditionalTokensStr: String

    Get additional tokens in string format

  51. def getBatchSize: Int
    Definition Classes
    HasBatchedAnnotate
  52. def getCaseSensitive: Boolean
    Definition Classes
    HasCaseSensitiveProperties
  53. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  54. def getConfigProtoBytes: Option[Array[Byte]]

  55. def getCustomPrompt: String

    Custom model prompt

    Custom model prompt

    Attributes
    protected
  56. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  57. def getDoSample: Boolean

    Definition Classes
    GPTGenerationParams
  58. def getEngine: String
    Definition Classes
    HasEngine
  59. def getIgnoreTokenIds: Array[Int]

    Definition Classes
    GPTGenerationParams
  60. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  61. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  62. def getMaxContextLength: Int

    Definition Classes
    GPTGenerationParams
  63. def getMaxNewTokens: Int

    Definition Classes
    GPTGenerationParams
  64. def getMaxTextLength: Int

  65. def getMlFrameworkType: String

    Get ML framework type

  66. def getModelIfNotSet: MedicalEncoderDecoderModel

  67. def getModelType: String

    Get model type

  68. def getNoRepeatNgramSize: Int

    Definition Classes
    GPTGenerationParams
  69. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  70. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  71. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  72. def getRandomSeed: Option[Int]

    Definition Classes
    GPTGenerationParams
  73. def getSignatures: Option[Map[String, String]]
  74. def getStopAtEos: Boolean

    Checks whether text generation stops when the end-of-sentence token is encountered.

  75. def getTopK: Int

    Definition Classes
    GPTGenerationParams
  76. def getUseCache: Boolean
  77. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  78. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  79. def hasParent: Boolean
    Definition Classes
    Model
  80. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  81. val ignoreTokenIds: IntArrayParam

    A list of token ids which are ignored in the decoder's output (Default: Array())

    A list of token ids which are ignored in the decoder's output (Default: Array())

    Definition Classes
    GPTGenerationParams
  82. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  83. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. val inputAnnotatorTypes: Array[String]

    Input annotator type : DOCUMENT, DOCUMENT

    Input annotator type : DOCUMENT, DOCUMENT

    Definition Classes
    MedicalTextGenerator → HasInputAnnotationCols
  85. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  86. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  87. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  88. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  89. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  90. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  91. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  92. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  93. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  94. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  95. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  96. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  97. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  98. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  99. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  100. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  101. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  102. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  103. val maxContextLength: IntParam

    Maximum length of context text.

    Maximum length of context text. (Default: 1024)

    Definition Classes
    GPTGenerationParams
  104. val maxNewTokens: IntParam

    Maximum number of new tokens to be generated (Default: 30)

    Maximum number of new tokens to be generated (Default: 30)

    Definition Classes
    GPTGenerationParams
  105. val maxTextLength: IntParam

    Maximum length of context text.

    Maximum length of context text. (Default: 1024)

  106. val merges: MapFeature[(String, String), Int]

    Holding merges.txt coming from RoBERTa model

  107. val mlFrameworkType: Param[String]

    ML framework type

  108. val modelType: Param[String]

    Model type

  109. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  110. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  111. val noRepeatNgramSize: IntParam

    If set to int > 0, all ngrams of that size can only occur once (Default: 0)

    If set to int > 0, all ngrams of that size can only occur once (Default: 0)

    Definition Classes
    GPTGenerationParams
  112. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  113. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  114. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    MedicalTextGenerator → ParamsAndFeaturesWritable
  115. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  116. val outputAnnotatorType: String

    Output annotator type : DOCUMENT

    Output annotator type : DOCUMENT

    Definition Classes
    MedicalTextGenerator → HasOutputAnnotatorType
  117. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  118. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  119. var parent: Estimator[MedicalQuestionAnswering]
    Definition Classes
    Model
  120. val randomSeed: Option[Int]

    Optional Random seed for the model.

    Optional Random seed for the model. Needs to be of type Long.

    Definition Classes
    GPTGenerationParams
  121. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  122. def set[T](feature: StructFeature[T], value: T): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  123. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  124. def set[T](feature: SetFeature[T], value: Set[T]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  125. def set[T](feature: ArrayFeature[T], value: Array[T]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  126. final def set(paramPair: ParamPair[_]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    Params
  127. final def set(param: String, value: Any): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    Params
  128. final def set[T](param: Param[T], value: T): MedicalTextGenerator.this.type
    Definition Classes
    Params
  129. def setAdditionalTokens(values: HashMap[Int, String]): MedicalTextGenerator.this.type

    Set additional tokens

  130. def setAdditionalTokens(value: Map[Int, String]): MedicalTextGenerator.this.type

    Set additional tokens

  131. def setBatchSize(size: Int): MedicalTextGenerator.this.type
    Definition Classes
    HasBatchedAnnotate
  132. def setCaseSensitive(value: Boolean): MedicalTextGenerator.this.type
    Definition Classes
    HasCaseSensitiveProperties
  133. def setConfigProtoBytes(bytes: Array[Int]): MedicalTextGenerator.this.type

  134. def setCustomPrompt(value: String): MedicalTextGenerator.this.type

    Set custom model prompt

  135. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  136. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  137. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  138. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  139. final def setDefault(paramPairs: ParamPair[_]*): MedicalTextGenerator.this.type
    Attributes
    protected
    Definition Classes
    Params
  140. final def setDefault[T](param: Param[T], value: T): MedicalTextGenerator.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  141. def setDoSample(value: Boolean): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  142. def setIgnoreTokenIds(tokenIds: Array[Int]): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  143. final def setInputCols(value: String*): MedicalTextGenerator.this.type
    Definition Classes
    HasInputAnnotationCols
  144. def setInputCols(value: Array[String]): MedicalTextGenerator.this.type
    Definition Classes
    HasInputAnnotationCols
  145. def setLazyAnnotator(value: Boolean): MedicalTextGenerator.this.type
    Definition Classes
    CanBeLazy
  146. def setMaxContextLength(value: Int): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  147. def setMaxNewTokens(value: Int): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  148. def setMaxTextLength(value: Int): MedicalTextGenerator.this.type

  149. def setMerges(value: Map[(String, String), Int]): MedicalTextGenerator.this.type

  150. def setMlFrameworkType(value: String): MedicalTextGenerator.this.type

    Set ML framework type

  151. def setModelIfNotSet(spark: SparkSession, model: MedicalEncoderDecoderModel): MedicalTextGenerator.this.type
  152. def setModelIfNotSet(spark: SparkSession, encoder: OnnxWrapper, decoder: OnnxWrapper, spp: SentencePieceWrapper): MedicalTextGenerator.this.type
  153. def setModelIfNotSet(spark: SparkSession, tfWrapper: TensorflowWrapper, spp: SentencePieceWrapper, useCache: Boolean): MedicalTextGenerator.this.type
  154. def setModelIfNotSet(spark: SparkSession, tfWrapper: TensorflowWrapper): MedicalTextGenerator.this.type

  155. def setModelType(value: String): MedicalTextGenerator.this.type

    Set model type

  156. def setNoRepeatNgramSize(value: Int): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  157. final def setOutputCol(value: String): MedicalTextGenerator.this.type
    Definition Classes
    HasOutputAnnotationCol
  158. def setParent(parent: Estimator[MedicalQuestionAnswering]): MedicalQuestionAnswering
    Definition Classes
    Model
  159. def setRandomSeed(value: Int): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  160. def setSignatures(value: Map[String, String]): MedicalTextGenerator.this.type

  161. def setStopAtEos(value: Boolean): MedicalTextGenerator.this.type

    Determines whether text generation stops when the end-of-sentence token is encountered.

  162. def setTopK(value: Int): MedicalTextGenerator.this.type

    Definition Classes
    GPTGenerationParams
  163. def setUseCache(value: Boolean): MedicalTextGenerator.this.type
  164. def setVocabulary(value: Map[String, Int]): MedicalTextGenerator.this.type

  165. val signatures: MapFeature[String, String]

    It contains TF model signatures for the laded saved model

  166. val stopAtEos: BooleanParam

    Stop text generation when the end-of-sentence token is encountered.

  167. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  168. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  169. val topK: IntParam

    The number of highest probability vocabulary tokens to consider

    The number of highest probability vocabulary tokens to consider

    Definition Classes
    GPTGenerationParams
  170. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  171. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  172. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  173. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  174. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  175. val uid: String
    Definition Classes
    MedicalTextGenerator → Identifiable
  176. val useCache: BooleanParam

    Cache internal state of the model to improve performance

  177. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  178. val vocabulary: MapFeature[String, Int]

    Vocabulary used to encode the words to ids with bpeTokenizer.encode

  179. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  180. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  181. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  182. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  183. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  184. def writeOnnxModel(path: String, spark: SparkSession, onnxWrapper: OnnxWrapper, suffix: String, fileName: String): Unit
    Definition Classes
    WriteOnnxModel
  185. def writeOnnxModels(path: String, spark: SparkSession, onnxWrappersWithNames: Seq[(OnnxWrapper, String)], suffix: String): Unit
    Definition Classes
    WriteOnnxModel
  186. def writeSentencePieceModel(path: String, spark: SparkSession, spp: SentencePieceWrapper, suffix: String, filename: String): Unit
    Definition Classes
    WriteSentencePieceModel
  187. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  188. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  189. 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 CheckLicense

Inherited from HasEngine

Inherited from WriteSentencePieceModel

Inherited from WriteOnnxModel

Inherited from WriteTensorflowModel

Inherited from HasBatchedAnnotate[MedicalQuestionAnswering]

Inherited from HasCaseSensitiveProperties

Inherited from GPTGenerationParams

Inherited from AnnotatorModel[MedicalQuestionAnswering]

Inherited from CanBeLazy

Inherited from RawAnnotator[MedicalQuestionAnswering]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[MedicalQuestionAnswering]

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

getParam

param

setParam

Ungrouped