object MedicalBertForSequenceClassification extends ReadablePretrainedBertForSequenceModel with ReadMedicalBertForSequenceClassification with Serializable
This is the companion object of MedicalBertForSequenceClassification. Please refer to that class for the documentation.
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- MedicalBertForSequenceClassification
- Serializable
- Serializable
- ReadMedicalBertForSequenceClassification
- ReadOnnxModel
- ReadTensorflowModel
- ReadablePretrainedBertForSequenceModel
- HasPretrained
- ParamsAndFeaturesReadable
- DefaultParamsReadable
- MLReadable
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def
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final
def
==(arg0: Any): Boolean
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def
addReader(reader: (MedicalBertForSequenceClassification, 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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val
defaultLang: String
- Definition Classes
- HasPretrained
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lazy val
defaultLoc: String
- Definition Classes
- ReadablePretrainedBertForSequenceModel → HasPretrained
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val
defaultModelName: Some[String]
- Definition Classes
- ReadablePretrainedBertForSequenceModel → HasPretrained
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final
def
isInstanceOf[T0]: Boolean
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def
load(path: String): MedicalBertForSequenceClassification
- Definition Classes
- MLReadable
- Annotations
- @Since( "1.6.0" )
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def
loadSavedModel(modelPath: String, spark: SparkSession): MedicalBertForSequenceClassification
- Definition Classes
- ReadMedicalBertForSequenceClassification
- def loadSavedModelOpenSource(bertForTokenClassifierPath: String, tfModelPath: String, spark: SparkSession): MedicalBertForSequenceClassification
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notify(): Unit
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final
def
notifyAll(): Unit
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val
onnxFile: String
- Definition Classes
- ReadMedicalBertForSequenceClassification → ReadOnnxModel
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def
pretrained(name: String, lang: String, remoteLoc: String): MedicalBertForSequenceClassification
Java compliant-overrides
Java compliant-overrides
- Definition Classes
- ReadablePretrainedBertForSequenceModel → HasPretrained
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def
pretrained(name: String, lang: String): MedicalBertForSequenceClassification
- Definition Classes
- ReadablePretrainedBertForSequenceModel → HasPretrained
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def
pretrained(name: String): MedicalBertForSequenceClassification
- Definition Classes
- ReadablePretrainedBertForSequenceModel → HasPretrained
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def
pretrained(): MedicalBertForSequenceClassification
- Definition Classes
- ReadablePretrainedBertForSequenceModel → HasPretrained
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def
read: MLReader[MedicalBertForSequenceClassification]
- Definition Classes
- ParamsAndFeaturesReadable → DefaultParamsReadable → MLReadable
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def
readModel(instance: MedicalBertForSequenceClassification, path: String, spark: SparkSession): Unit
- Definition Classes
- ReadMedicalBertForSequenceClassification
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def
readOnnxModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, modelName: Option[String], tmpFolder: Option[String], dataFilePostfix: Option[String]): OnnxWrapper
- Definition Classes
- ReadOnnxModel
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def
readOnnxModels(path: String, spark: SparkSession, modelNames: Seq[String], suffix: String, zipped: Boolean, useBundle: Boolean, dataFilePostfix: String): Map[String, OnnxWrapper]
- Definition Classes
- ReadOnnxModel
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def
readTensorflowChkPoints(path: String, spark: SparkSession, suffix: String, zipped: Boolean, tags: Array[String], initAllTables: Boolean): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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def
readTensorflowHub(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, tags: Array[String]): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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def
readTensorflowModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, tags: Array[String], initAllTables: Boolean, savedSignatures: Option[Map[String, String]]): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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def
readTensorflowWithSPModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, tags: Array[String], initAllTables: Boolean, loadSP: Boolean): TensorflowWrapper
- Definition Classes
- ReadTensorflowModel
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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val
tfFile: String
- Definition Classes
- ReadMedicalBertForSequenceClassification → ReadTensorflowModel
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def
toString(): String
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final
def
wait(): Unit
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wait(arg0: Long, arg1: Int): Unit
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