Value Members

1.  final def !=(arg0: Any): Boolean

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2.  final def ##(): Int

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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 chatTemplate: Param[String]

6.  def clone(): AnyRef

   Attributes

   protected[lang]

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   @throws( ... ) @native()

7.  val defragmentationThreshold: FloatParam

8.  val embedding: BooleanParam

9.  final def eq(arg0: AnyRef): Boolean

   Definition Classes

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10.  def equals(arg0: Any): Boolean

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11.  def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )

12.  val flashAttention: BooleanParam

13.  def getChatTemplate: String

14.  final def getClass(): Class[_]

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    @native()

15.  def getDefragmentationThreshold: Float

16.  def getEmbedding: Boolean

17.  def getFlashAttention: Boolean

18.  def getMainGpu: Int

19.  def getMetadata: String

    Get the metadata for the model

20.  def getMetadataMap: Map[String, Map[String, String]]
21.  def getModelDraft: String

22.  def getModelParameters: ModelParameters

    Attributes

    protected

23.  def getNBatch: Int

24.  def getNCtx: Int

25.  def getNDraft: Int

26.  def getNGpuLayers: Int

27.  def getNGpuLayersDraft: Int

28.  def getNThreads: Int

29.  def getNThreadsBatch: Int

30.  def getNUbatch: Int

31.  def getNoKvOffload: Boolean

32.  def getNuma: String

33.  def getPoolingType: String

34.  def getRopeFreqBase: Float

35.  def getRopeFreqScale: Float

36.  def getRopeScalingType: String

37.  def getSplitMode: String

38.  def getSystemPrompt: String

39.  def getUseMlock: Boolean

40.  def getUseMmap: Boolean

41.  def getYarnAttnFactor: Float

42.  def getYarnBetaFast: Float

43.  def getYarnBetaSlow: Float

44.  def getYarnExtFactor: Float

45.  def getYarnOrigCtx: Int

46.  val gpuSplitMode: Param[String]

    Set how to split the model across GPUs

    Set how to split the model across GPUs

    • NONE: No GPU split
    • LAYER: Split the model across GPUs by layer
    • ROW: Split the model across GPUs by rows
47.  def hashCode(): Int

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48.  final def isInstanceOf[T0]: Boolean

    Definition Classes

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49.  val logger: Logger

    Attributes

    protected

50.  val mainGpu: IntParam

51.  val metadata: (HasLlamaCppModelProperties.this)#ProtectedParam[String]
52.  val modelDraft: Param[String]

53.  val nBatch: IntParam

54.  val nCtx: IntParam

55.  val nDraft: IntParam

56.  val nGpuLayers: IntParam

57.  val nGpuLayersDraft: IntParam

58.  val nThreads: IntParam

59.  val nThreadsBatch: IntParam

60.  val nUbatch: IntParam

61.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

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62.  val noKvOffload: BooleanParam

63.  final def notify(): Unit

    Definition Classes

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    @native()

64.  final def notifyAll(): Unit

    Definition Classes

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    @native()

65.  val numaStrategy: Param[String]

    Set optimization strategies that help on some NUMA systems (if available)

    Set optimization strategies that help on some NUMA systems (if available)

    Available Strategies:

    • DISABLED: No NUMA optimizations
    • DISTRIBUTE: Spread execution evenly over all
    • ISOLATE: Only spawn threads on CPUs on the node that execution started on
    • NUMA_CTL: Use the CPU map provided by numactl
    • MIRROR: Mirrors the model across NUMA nodes
66.  val poolingType: Param[String]

    Set the pooling type for embeddings, use model default if unspecified

    Set the pooling type for embeddings, use model default if unspecified

    • 0 NONE: Don't use any pooling
    • 1 MEAN: Mean Pooling
    • 2 CLS: Choose the CLS token
    • 3 LAST: Choose the last token
67.  val ropeFreqBase: FloatParam

68.  val ropeFreqScale: FloatParam

69.  val ropeScalingType: Param[String]

    Set the RoPE frequency scaling method, defaults to linear unless specified by the model.

    Set the RoPE frequency scaling method, defaults to linear unless specified by the model.

    • UNSPECIFIED: Don't use any scaling
    • LINEAR: Linear scaling
    • YARN: YaRN RoPE scaling
70.  def setChatTemplate(chatTemplate: String): HasLlamaCppModelProperties.this

    The chat template to use

71.  def setDefragmentationThreshold(defragThold: Float): HasLlamaCppModelProperties.this

    Set the KV cache defragmentation threshold

72.  def setEmbedding(embedding: Boolean): HasLlamaCppModelProperties.this

    Whether to load model with embedding support

73.  def setFlashAttention(flashAttention: Boolean): HasLlamaCppModelProperties.this

    Whether to enable Flash Attention

74.  def setGpuSplitMode(splitMode: String): HasLlamaCppModelProperties.this

    Set how to split the model across GPUs

    Set how to split the model across GPUs

    • NONE: No GPU split -LAYER: Split the model across GPUs by layer 2. ROW: Split the model across GPUs by rows
75.  def setMainGpu(mainGpu: Int): HasLlamaCppModelProperties.this

    Set the GPU that is used for scratch and small tensors

76.  def setMetadata(metadata: String): HasLlamaCppModelProperties.this

    Set the metadata for the model

77.  def setModelDraft(modelDraft: String): HasLlamaCppModelProperties.this

    Set the draft model for speculative decoding

78.  def setNBatch(nBatch: Int): HasLlamaCppModelProperties.this

    Set the logical batch size for prompt processing (must be >=32 to use BLAS)

79.  def setNCtx(nCtx: Int): HasLlamaCppModelProperties.this

    Set the size of the prompt context

80.  def setNDraft(nDraft: Int): HasLlamaCppModelProperties.this

    Set the number of tokens to draft for speculative decoding

81.  def setNGpuLayers(nGpuLayers: Int): HasLlamaCppModelProperties.this

    Set the number of layers to store in VRAM (-1 - use default)

82.  def setNGpuLayersDraft(nGpuLayersDraft: Int): HasLlamaCppModelProperties.this

    Set the number of layers to store in VRAM for the draft model (-1 - use default)

83.  def setNThreads(nThreads: Int): HasLlamaCppModelProperties.this

    Set the number of threads to use during generation

84.  def setNThreadsBatch(nThreadsBatch: Int): HasLlamaCppModelProperties.this

    Set the number of threads to use during batch and prompt processing

85.  def setNUbatch(nUbatch: Int): HasLlamaCppModelProperties.this

    Set the physical batch size for prompt processing (must be >=32 to use BLAS)

86.  def setNoKvOffload(noKvOffload: Boolean): HasLlamaCppModelProperties.this

    Whether to disable KV offload

87.  def setNumaStrategy(numa: String): HasLlamaCppModelProperties.this

    Set optimization strategies that help on some NUMA systems (if available)

    Set optimization strategies that help on some NUMA systems (if available)

    Available Strategies:

    • DISABLED: No NUMA optimizations
    • DISTRIBUTE: spread execution evenly over all
    • ISOLATE: only spawn threads on CPUs on the node that execution started on
    • NUMA_CTL: use the CPU map provided by numactl
    • MIRROR: Mirrors the model across NUMA nodes
88.  def setPoolingType(poolingType: String): HasLlamaCppModelProperties.this

    Set the pooling type for embeddings, use model default if unspecified.

    Set the pooling type for embeddings, use model default if unspecified.

    Possible values:

    • NONE: No pooling
    • MEAN: Mean pooling
    • CLS: Choose the CLS token
    • LAST: Choose the last token
    • RANK: For reranking
89.  def setRopeFreqBase(ropeFreqBase: Float): HasLlamaCppModelProperties.this

    Set the RoPE base frequency, used by NTK-aware scaling

90.  def setRopeFreqScale(ropeFreqScale: Float): HasLlamaCppModelProperties.this

    Set the RoPE frequency scaling factor, expands context by a factor of 1/N

91.  def setRopeScalingType(ropeScalingType: String): HasLlamaCppModelProperties.this

    Set the RoPE frequency scaling method, defaults to linear unless specified by the model.

    Set the RoPE frequency scaling method, defaults to linear unless specified by the model.

    • NONE: Don't use any scaling
    • LINEAR: Linear scaling
    • YARN: YaRN RoPE scaling
92.  def setSystemPrompt(systemPrompt: String): HasLlamaCppModelProperties.this

    Set a system prompt to use

93.  def setUseMlock(useMlock: Boolean): HasLlamaCppModelProperties.this

    Whether to force the system to keep model in RAM rather than swapping or compressing

94.  def setUseMmap(useMmap: Boolean): HasLlamaCppModelProperties.this

    Whether to use memory-map model (faster load but may increase pageouts if not using mlock)

95.  def setYarnAttnFactor(yarnAttnFactor: Float): HasLlamaCppModelProperties.this

    Set the YaRN scale sqrt(t) or attention magnitude

96.  def setYarnBetaFast(yarnBetaFast: Float): HasLlamaCppModelProperties.this

    Set the YaRN low correction dim or beta

97.  def setYarnBetaSlow(yarnBetaSlow: Float): HasLlamaCppModelProperties.this

    Set the YaRN high correction dim or alpha

98.  def setYarnExtFactor(yarnExtFactor: Float): HasLlamaCppModelProperties.this

    Set the YaRN extrapolation mix factor

99.  def setYarnOrigCtx(yarnOrigCtx: Int): HasLlamaCppModelProperties.this

    Set the YaRN original context size of model

100.  final def synchronized[T0](arg0: ⇒ T0): T0

     Definition Classes

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101.  val systemPrompt: Param[String]

102.  def toString(): String

     Definition Classes

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103.  val useMlock: BooleanParam

104.  val useMmap: BooleanParam

105.  final def wait(): Unit

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     @throws( ... )

106.  final def wait(arg0: Long, arg1: Int): Unit

     Definition Classes

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     @throws( ... )

107.  final def wait(arg0: Long): Unit

     Definition Classes

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108.  val yarnAttnFactor: FloatParam

109.  val yarnBetaFast: FloatParam

110.  val yarnBetaSlow: FloatParam

111.  val yarnExtFactor: FloatParam

112.  val yarnOrigCtx: IntParam