Packages

class ModernBertEmbeddings extends AnnotatorModel[ModernBertEmbeddings] with HasBatchedAnnotate[ModernBertEmbeddings] with WriteTensorflowModel with WriteOnnxModel with WriteOpenvinoModel with HasEmbeddingsProperties with HasStorageRef with HasCaseSensitiveProperties with HasEngine

Token-level embeddings using ModernBERT. ModernBERT is a state-of-the-art encoder model designed for improved efficiency and performance compared to traditional BERT models.

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

val embeddings = ModernBertEmbeddings.pretrained()
  .setInputCols("token", "document")
  .setOutputCol("modernbert_embeddings")

The default model is "modernbert-base", if no name is provided.

For available pretrained models please see the Models Hub.

For extended examples of usage, see the Examples and the ModernBertEmbeddingsTestSpec. To see which models are compatible and how to import them see https://github.com/JohnSnowLabs/spark-nlp/discussions/5669.

Sources :

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Applications

https://huggingface.co/answerdotai/ModernBERT-base

Paper abstract

We introduce ModernBERT, a modernized bidirectional encoder model that is 8x faster, uses 5x less memory, and achieves better downstream performance than traditional BERT models. ModernBERT incorporates modern improvements including Flash Attention, unpadding, and GeGLU activation functions. The model supports sequence lengths up to 8192 tokens while maintaining competitive performance on tasks requiring long context understanding.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.embeddings.ModernBertEmbeddings
import com.johnsnowlabs.nlp.EmbeddingsFinisher
import org.apache.spark.ml.Pipeline

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

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

val embeddings = ModernBertEmbeddings.pretrained("modernbert-base", "en")
  .setInputCols("token", "document")
  .setOutputCol("modernbert_embeddings")

val embeddingsFinisher = new EmbeddingsFinisher()
  .setInputCols("modernbert_embeddings")
  .setOutputCols("finished_embeddings")
  .setOutputAsVector(true)

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

val data = Seq("This is a sentence.").toDF("text")
val result = pipeline.fit(data).transform(data)

result.selectExpr("explode(finished_embeddings) as result").show(5, 80)
+--------------------------------------------------------------------------------+
|                                                                          result|
+--------------------------------------------------------------------------------+
|[-2.3497989177703857,0.480538547039032,-0.3238905668258667,-1.612930893898010...|
|[-2.1357314586639404,0.32984697818756104,-0.6032363176345825,-1.6791689395904...|
|[-1.8244884014129639,-0.27088963985443115,-1.059438943862915,-0.9817547798156...|
|[-1.1648050546646118,-0.4725411534309387,-0.5938255786895752,-1.5780693292617...|
|[-0.9125322699546814,0.4563939869403839,-0.3975459933280945,-1.81611204147338...|
+--------------------------------------------------------------------------------+
See also

ModernBertSentenceEmbeddings for sentence-level embeddings

ModernBertForTokenClassification For ModernBertEmbeddings with a token classification layer on top

Annotators Main Page for a list of transformer based embeddings

Linear Supertypes
HasEngine, HasCaseSensitiveProperties, HasStorageRef, HasEmbeddingsProperties, HasProtectedParams, WriteOpenvinoModel, WriteOnnxModel, WriteTensorflowModel, HasBatchedAnnotate[ModernBertEmbeddings], AnnotatorModel[ModernBertEmbeddings], CanBeLazy, RawAnnotator[ModernBertEmbeddings], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[ModernBertEmbeddings], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ModernBertEmbeddings
  2. HasEngine
  3. HasCaseSensitiveProperties
  4. HasStorageRef
  5. HasEmbeddingsProperties
  6. HasProtectedParams
  7. WriteOpenvinoModel
  8. WriteOnnxModel
  9. WriteTensorflowModel
  10. HasBatchedAnnotate
  11. AnnotatorModel
  12. CanBeLazy
  13. RawAnnotator
  14. HasOutputAnnotationCol
  15. HasInputAnnotationCols
  16. HasOutputAnnotatorType
  17. ParamsAndFeaturesWritable
  18. HasFeatures
  19. DefaultParamsWritable
  20. MLWritable
  21. Model
  22. Transformer
  23. PipelineStage
  24. Logging
  25. Params
  26. Serializable
  27. Serializable
  28. Identifiable
  29. AnyRef
  30. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ModernBertEmbeddings()

    Annotator reference id.

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

  2. new ModernBertEmbeddings(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. implicit class ProtectedParam[T] extends Param[T]
    Definition Classes
    HasProtectedParams
  2. type AnnotationContent = Seq[Row]

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    Attributes
    protected
    Definition Classes
    AnnotatorModel
  3. 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. val addedTokens: MapFeature[String, Int]

    Added tokens for the BPE tokenizer

  11. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    ModernBertEmbeddings → AnnotatorModel
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. 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
    ModernBertEmbeddings → HasBatchedAnnotate
  14. def batchProcess(rows: Iterator[_]): Iterator[Row]
    Definition Classes
    HasBatchedAnnotate
  15. val batchSize: IntParam

    Size of every batch (Default depends on model).

    Size of every batch (Default depends on model).

    Definition Classes
    HasBatchedAnnotate
  16. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  17. val caseSensitive: BooleanParam

    Whether to ignore case in index lookups (Default depends on model)

    Whether to ignore case in index lookups (Default depends on model)

    Definition Classes
    HasCaseSensitiveProperties
  18. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  19. final def clear(param: Param[_]): ModernBertEmbeddings.this.type
    Definition Classes
    Params
  20. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  21. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

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

  22. def copy(extra: ParamMap): ModernBertEmbeddings

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  23. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  24. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  25. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  26. val dimension: ProtectedParam[Int]

    Number of embedding dimensions (Default depends on model)

    Number of embedding dimensions (Default depends on model)

    Definition Classes
    HasEmbeddingsProperties
  27. val engine: Param[String]

    This param is set internally once via loadSavedModel.

    This param is set internally once via loadSavedModel. That's why there is no setter

    Definition Classes
    HasEngine
  28. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  29. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  30. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  31. def explainParams(): String
    Definition Classes
    Params
  32. final val extraInputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  33. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  34. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  35. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  36. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  37. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  38. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  39. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  40. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  42. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  44. def getBatchSize: Int

    Size of every batch.

    Size of every batch.

    Definition Classes
    HasBatchedAnnotate
  45. def getCaseSensitive: Boolean

    Definition Classes
    HasCaseSensitiveProperties
  46. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  47. def getConfigProtoBytes: Option[Array[Byte]]

  48. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  49. def getDimension: Int

    Definition Classes
    HasEmbeddingsProperties
  50. def getEngine: String

    Definition Classes
    HasEngine
  51. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  52. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  53. def getMaxSentenceLength: Int

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

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  57. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  58. def getSignatures: Option[Map[String, String]]

  59. def getStorageRef: String
    Definition Classes
    HasStorageRef
  60. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  61. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  62. def hasParent: Boolean
    Definition Classes
    Model
  63. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  64. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  65. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. val inputAnnotatorTypes: Array[String]

    Input Annotator Types: DOCUMENT, TOKEN

    Input Annotator Types: DOCUMENT, TOKEN

    Definition Classes
    ModernBertEmbeddings → HasInputAnnotationCols
  67. 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
  68. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  69. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  70. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  71. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  72. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  73. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  74. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  81. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. val maxSentenceLength: IntParam

    Max sentence length to process (Default: 8192)

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

    Merges used by the BPE tokenizer

  87. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  88. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  89. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  90. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  91. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    ModernBertEmbeddings → ParamsAndFeaturesWritable
  92. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  93. val outputAnnotatorType: AnnotatorType

    Output Annotator Types: WORD_EMBEDDINGS

    Output Annotator Types: WORD_EMBEDDINGS

    Definition Classes
    ModernBertEmbeddings → HasOutputAnnotatorType
  94. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  95. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  96. var parent: Estimator[ModernBertEmbeddings]
    Definition Classes
    Model
  97. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  98. def sentenceEndTokenId: Int

  99. def sentenceStartTokenId: Int

  100. def set[T](param: ProtectedParam[T], value: T): ModernBertEmbeddings.this.type

    Sets the value for a protected Param.

    Sets the value for a protected Param.

    If the parameter was already set, it will not be set again. Default values do not count as a set value and can be overridden.

    T

    Type of the parameter

    param

    Protected parameter to set

    value

    Value for the parameter

    returns

    This object

    Definition Classes
    HasProtectedParams
  101. def set[T](feature: StructFeature[T], value: T): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. def set[T](feature: SetFeature[T], value: Set[T]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  104. def set[T](feature: ArrayFeature[T], value: Array[T]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. final def set(paramPair: ParamPair[_]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    Params
  106. final def set(param: String, value: Any): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    Params
  107. final def set[T](param: Param[T], value: T): ModernBertEmbeddings.this.type
    Definition Classes
    Params
  108. def setAddedTokens(value: Map[String, Int]): ModernBertEmbeddings.this.type

  109. def setBatchSize(size: Int): ModernBertEmbeddings.this.type

    Size of every batch.

    Size of every batch.

    Definition Classes
    HasBatchedAnnotate
  110. def setCaseSensitive(value: Boolean): ModernBertEmbeddings.this.type

    Whether to lowercase tokens or not

    Whether to lowercase tokens or not

    Definition Classes
    ModernBertEmbeddings → HasCaseSensitiveProperties
  111. def setConfigProtoBytes(bytes: Array[Int]): ModernBertEmbeddings.this.type

  112. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  113. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  114. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  115. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  116. final def setDefault(paramPairs: ParamPair[_]*): ModernBertEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    Params
  117. final def setDefault[T](param: Param[T], value: T): ModernBertEmbeddings.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  118. def setDimension(value: Int): ModernBertEmbeddings.this.type

    Set Embeddings dimensions for the ModernBERT model Only possible to set this when the first time is saved dimension is not changeable, it comes from ModernBERT config file

    Set Embeddings dimensions for the ModernBERT model Only possible to set this when the first time is saved dimension is not changeable, it comes from ModernBERT config file

    Definition Classes
    ModernBertEmbeddings → HasEmbeddingsProperties
  119. def setExtraInputCols(value: Array[String]): ModernBertEmbeddings.this.type
    Definition Classes
    HasInputAnnotationCols
  120. final def setInputCols(value: String*): ModernBertEmbeddings.this.type
    Definition Classes
    HasInputAnnotationCols
  121. def setInputCols(value: Array[String]): ModernBertEmbeddings.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  122. def setLazyAnnotator(value: Boolean): ModernBertEmbeddings.this.type
    Definition Classes
    CanBeLazy
  123. def setMaxSentenceLength(value: Int): ModernBertEmbeddings.this.type

  124. def setMerges(value: Map[(String, String), Int]): ModernBertEmbeddings.this.type

  125. def setModelIfNotSet(spark: SparkSession, tensorflowWrapper: Option[TensorflowWrapper], onnxWrapper: Option[OnnxWrapper], openvinoWrapper: Option[OpenvinoWrapper]): ModernBertEmbeddings

  126. final def setOutputCol(value: String): ModernBertEmbeddings.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  127. def setParent(parent: Estimator[ModernBertEmbeddings]): ModernBertEmbeddings
    Definition Classes
    Model
  128. def setSignatures(value: Map[String, String]): ModernBertEmbeddings.this.type

  129. def setStorageRef(value: String): ModernBertEmbeddings.this.type
    Definition Classes
    HasStorageRef
  130. def setVocabulary(value: Map[String, Int]): ModernBertEmbeddings.this.type

  131. val signatures: MapFeature[String, String]

    It contains TF model signatures for the laded saved model

  132. val storageRef: Param[String]

    Unique identifier for storage (Default: this.uid)

    Unique identifier for storage (Default: this.uid)

    Definition Classes
    HasStorageRef
  133. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  134. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  135. final def transform(dataset: Dataset[_]): DataFrame

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    dataset

    Dataset[Row]

    Definition Classes
    AnnotatorModel → Transformer
  136. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  137. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  138. 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
  139. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  140. val uid: String
    Definition Classes
    ModernBertEmbeddings → Identifiable
  141. 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
  142. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  143. val vocabulary: MapFeature[String, Int]

    Vocabulary used to encode the words to ids with BPE tokenizer

  144. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  145. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  146. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  147. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  148. def wrapEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column
    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  149. def wrapSentenceEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column
    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  150. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  151. def writeOnnxModel(path: String, spark: SparkSession, onnxWrapper: OnnxWrapper, suffix: String, fileName: String): Unit
    Definition Classes
    WriteOnnxModel
  152. def writeOnnxModels(path: String, spark: SparkSession, onnxWrappersWithNames: Seq[(OnnxWrapper, String)], suffix: String): Unit
    Definition Classes
    WriteOnnxModel
  153. def writeOpenvinoModel(path: String, spark: SparkSession, openvinoWrapper: OpenvinoWrapper, suffix: String, fileName: String): Unit
    Definition Classes
    WriteOpenvinoModel
  154. def writeOpenvinoModels(path: String, spark: SparkSession, ovWrappersWithNames: Seq[(OpenvinoWrapper, String)], suffix: String): Unit
    Definition Classes
    WriteOpenvinoModel
  155. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String = "_use"): Unit
    Definition Classes
    WriteTensorflowModel
  156. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None): Unit
    Definition Classes
    WriteTensorflowModel
  157. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None, savedSignatures: Option[Map[String, String]] = None): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from HasEngine

Inherited from HasCaseSensitiveProperties

Inherited from HasStorageRef

Inherited from HasEmbeddingsProperties

Inherited from HasProtectedParams

Inherited from WriteOpenvinoModel

Inherited from WriteOnnxModel

Inherited from WriteTensorflowModel

Inherited from HasBatchedAnnotate[ModernBertEmbeddings]

Inherited from AnnotatorModel[ModernBertEmbeddings]

Inherited from CanBeLazy

Inherited from RawAnnotator[ModernBertEmbeddings]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[ModernBertEmbeddings]

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

A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters