o
com.johnsnowlabs.nlp.annotators.classifier.dl
RoBertaForSequenceClassification
Companion class RoBertaForSequenceClassification
object RoBertaForSequenceClassification extends ReadablePretrainedRoBertaForSequenceModel with ReadRoBertaForSequenceDLModel with Serializable
This is the companion object of RoBertaForSequenceClassification. Please refer to that class for the documentation.
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- RoBertaForSequenceClassification
- Serializable
- Serializable
- ReadRoBertaForSequenceDLModel
- ReadOnnxModel
- ReadTensorflowModel
- ReadablePretrainedRoBertaForSequenceModel
- HasPretrained
- ParamsAndFeaturesReadable
- DefaultParamsReadable
- MLReadable
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final
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!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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def
addReader(reader: (RoBertaForSequenceClassification, String, SparkSession) ⇒ Unit): Unit
- Definition Classes
- ParamsAndFeaturesReadable
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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- protected[lang]
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val
defaultLang: String
- Definition Classes
- HasPretrained
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lazy val
defaultLoc: String
- Definition Classes
- HasPretrained
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val
defaultModelName: Some[String]
- Definition Classes
- ReadablePretrainedRoBertaForSequenceModel → HasPretrained
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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finalize(): Unit
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hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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def
load(path: String): RoBertaForSequenceClassification
- Definition Classes
- MLReadable
- Annotations
- @Since( "1.6.0" )
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def
loadSavedModel(modelPath: String, spark: SparkSession): RoBertaForSequenceClassification
- Definition Classes
- ReadRoBertaForSequenceDLModel
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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val
onnxFile: String
- Definition Classes
- ReadRoBertaForSequenceDLModel → ReadOnnxModel
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def
pretrained(name: String, lang: String, remoteLoc: String): RoBertaForSequenceClassification
Java default argument interoperability
Java default argument interoperability
- Definition Classes
- ReadablePretrainedRoBertaForSequenceModel → HasPretrained
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def
pretrained(name: String, lang: String): RoBertaForSequenceClassification
- Definition Classes
- ReadablePretrainedRoBertaForSequenceModel → HasPretrained
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def
pretrained(name: String): RoBertaForSequenceClassification
- Definition Classes
- ReadablePretrainedRoBertaForSequenceModel → HasPretrained
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def
pretrained(): RoBertaForSequenceClassification
Java compliant-overrides
Java compliant-overrides
- Definition Classes
- ReadablePretrainedRoBertaForSequenceModel → HasPretrained
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def
read: MLReader[RoBertaForSequenceClassification]
- Definition Classes
- ParamsAndFeaturesReadable → DefaultParamsReadable → MLReadable
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def
readModel(instance: RoBertaForSequenceClassification, path: String, spark: SparkSession): Unit
- Definition Classes
- ReadRoBertaForSequenceDLModel
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def
readOnnxModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean = true, useBundle: Boolean = false, modelName: Option[String] = None, tmpFolder: Option[String] = None, dataFilePostfix: Option[String] = None): OnnxWrapper
- Definition Classes
- ReadOnnxModel
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def
readOnnxModels(path: String, spark: SparkSession, modelNames: Seq[String], suffix: String, zipped: Boolean = true, useBundle: Boolean = false, dataFilePostfix: String = "_data"): Map[String, OnnxWrapper]
- Definition Classes
- ReadOnnxModel
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def
readTensorflowChkPoints(path: String, spark: SparkSession, suffix: String, zipped: Boolean = true, tags: Array[String] = Array.empty, initAllTables: Boolean = false): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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def
readTensorflowHub(path: String, spark: SparkSession, suffix: String, zipped: Boolean = true, useBundle: Boolean = false, tags: Array[String] = Array.empty): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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def
readTensorflowModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean = true, useBundle: Boolean = false, tags: Array[String] = Array.empty, initAllTables: Boolean = false, savedSignatures: Option[Map[String, String]] = None): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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def
readTensorflowWithSPModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean = true, useBundle: Boolean = false, tags: Array[String] = Array.empty, initAllTables: Boolean = false, loadSP: Boolean = false): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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val
tfFile: String
- Definition Classes
- ReadRoBertaForSequenceDLModel → ReadTensorflowModel
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def
toString(): String
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final
def
wait(): Unit
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def
wait(arg0: Long, arg1: Int): Unit
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wait(arg0: Long): Unit
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