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com.johnsnowlabs.nlp

HasGeneratorProperties

trait HasGeneratorProperties extends AnyRef

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Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
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  2. final def ##: Int
    Definition Classes
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. val beamSize: IntParam

    Beam size for the beam search algorithm (Default: 4)

  6. def clone(): AnyRef
    Attributes
    protected[lang]
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    @throws(classOf[java.lang.CloneNotSupportedException]) @HotSpotIntrinsicCandidate() @native()
  7. val doSample: BooleanParam

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

  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
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  9. def equals(arg0: AnyRef): Boolean
    Definition Classes
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  10. def getBeamSize: Int

  11. final def getClass(): Class[_ <: AnyRef]
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    @HotSpotIntrinsicCandidate() @native()
  12. def getDoSample: Boolean

  13. def getMaxOutputLength: Int

  14. def getMinOutputLength: Int

  15. def getNReturnSequences: Int

  16. def getNoRepeatNgramSize: Int

  17. def getRandomSeed: Option[Long]

  18. def getRepetitionPenalty: Double

  19. def getStopTokenIds: Array[Int]

  20. def getTask: Option[String]

  21. def getTemperature: Double

  22. def getTopK: Int

  23. def getTopP: Double

  24. def hashCode(): Int
    Definition Classes
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    @HotSpotIntrinsicCandidate() @native()
  25. final def isInstanceOf[T0]: Boolean
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  26. val maxInputLength: IntParam

    max length of the input sequence (Default: 0)

  27. val maxOutputLength: IntParam

    Maximum length of the sequence to be generated (Default: 20)

  28. val minOutputLength: IntParam

    Minimum length of the sequence to be generated (Default: 0)

  29. val nReturnSequences: IntParam

    The number of sequences to return from the beam search.

  30. final def ne(arg0: AnyRef): Boolean
    Definition Classes
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  31. val noRepeatNgramSize: IntParam

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

  32. final def notify(): Unit
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    @HotSpotIntrinsicCandidate() @native()
  33. final def notifyAll(): Unit
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    @HotSpotIntrinsicCandidate() @native()
  34. val randomSeed: Option[Long]

    Optional Random seed for the model.

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

  35. val repetitionPenalty: DoubleParam

    The parameter for repetition penalty (Default: 1.0).

    The parameter for repetition penalty (Default: 1.0). 1.0 means no penalty. See this paper for more details.

  36. def setBeamSize(beamNum: Int): HasGeneratorProperties.this

  37. def setDoSample(value: Boolean): HasGeneratorProperties.this

  38. def setMaxInputLength(value: Int): HasGeneratorProperties.this
  39. def setMaxOutputLength(value: Int): HasGeneratorProperties.this

  40. def setMinOutputLength(value: Int): HasGeneratorProperties.this

  41. def setNReturnSequences(beamNum: Int): HasGeneratorProperties.this

  42. def setNoRepeatNgramSize(value: Int): HasGeneratorProperties.this

  43. def setRandomSeed(value: Long): HasGeneratorProperties.this

  44. def setRepetitionPenalty(value: Double): HasGeneratorProperties.this

  45. def setStopTokenIds(value: Array[Int]): HasGeneratorProperties.this

  46. def setTask(value: String): HasGeneratorProperties.this

  47. def setTemperature(value: Double): HasGeneratorProperties.this

  48. def setTopK(value: Int): HasGeneratorProperties.this

  49. def setTopP(value: Double): HasGeneratorProperties.this

  50. val stopTokenIds: IntArrayParam

    Stop tokens to terminate the generation

  51. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
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  52. val task: Param[String]

    Set transformer task, e.g.

    Set transformer task, e.g. "summarize:" (Default: "").

  53. val temperature: DoubleParam

    The value used to module the next token probabilities (Default: 1.0)

  54. def toString(): String
    Definition Classes
    AnyRef → Any
  55. val topK: IntParam

    The number of highest probability vocabulary tokens to keep for top-k-filtering (Default: 50)

  56. val topP: DoubleParam

    If set to float < 1.0, only the most probable tokens with probabilities that add up to topP or higher are kept for generation (Default: 1.0)

  57. final def wait(arg0: Long, arg1: Int): Unit
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    @throws(classOf[java.lang.InterruptedException])
  58. final def wait(arg0: Long): Unit
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    @throws(classOf[java.lang.InterruptedException]) @native()
  59. final def wait(): Unit
    Definition Classes
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    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
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    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

    (Since version 9)

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