Packages

class AutoGGUFVisionModel extends AnnotatorModel[AutoGGUFVisionModel] with HasBatchedAnnotateTextImage[AutoGGUFVisionModel] with HasEngine with HasLlamaCppModelProperties with HasLlamaCppInferenceProperties with HasProtectedParams

Multimodal annotator that uses the llama.cpp library to generate text completions with large language models. It supports ingesting images for captioning.

At the moment only CLIP based models are supported.

For settable parameters, and their explanations, see HasLlamaCppInferenceProperties, HasLlamaCppModelProperties and refer to the llama.cpp documentation of server.cpp for more information.

If the parameters are not set, the annotator will default to use the parameters provided by the model.

This annotator expects a column of annotator type AnnotationImage for the image and Annotation for the caption. Note that the image bytes in the image annotation need to be raw image bytes without preprocessing. We provide the helper function ImageAssembler.loadImagesAsBytes to load the image bytes from a directory.

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

val autoGGUFVisionModel = AutoGGUFVisionModel.pretrained()
  .setInputCols("image', "document")
  .setOutputCol("completions")

The default model is "llava_v1.5_7b_Q4_0_gguf", if no name is provided.

For available pretrained models please see the Models Hub.

For extended examples of usage, see the AutoGGUFVisionModelTest and the example notebook.

Note

To use GPU inference with this annotator, make sure to use the Spark NLP GPU package and set the number of GPU layers with the setNGpuLayers method.

When using larger models, we recommend adjusting GPU usage with setNCtx and setNGpuLayers according to your hardware to avoid out-of-memory errors.

Example

import com.johnsnowlabs.nlp.ImageAssembler
import com.johnsnowlabs.nlp.annotator._
import com.johnsnowlabs.nlp.base._
import org.apache.spark.ml.Pipeline
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.functions.lit

val documentAssembler = new DocumentAssembler()
  .setInputCol("caption")
  .setOutputCol("caption_document")

val imageAssembler = new ImageAssembler()
  .setInputCol("image")
  .setOutputCol("image_assembler")

val imagesPath = "src/test/resources/image/"
val data: DataFrame = ImageAssembler
  .loadImagesAsBytes(ResourceHelper.spark, imagesPath)
  .withColumn("caption", lit("Caption this image.")) // Add a caption to each image.

val nPredict = 40
val model = AutoGGUFVisionModel.pretrained()
  .setInputCols("caption_document", "image_assembler")
  .setOutputCol("completions")
  .setBatchSize(4)
  .setNGpuLayers(99)
  .setNCtx(4096)
  .setMinKeep(0)
  .setMinP(0.05f)
  .setNPredict(nPredict)
  .setNProbs(0)
  .setPenalizeNl(false)
  .setRepeatLastN(256)
  .setRepeatPenalty(1.18f)
  .setStopStrings(Array("</s>", "Llama:", "User:"))
  .setTemperature(0.05f)
  .setTfsZ(1)
  .setTypicalP(1)
  .setTopK(40)
  .setTopP(0.95f)

val pipeline = new Pipeline().setStages(Array(documentAssembler, imageAssembler, model))
pipeline
  .fit(data)
  .transform(data)
  .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "completions.result")
  .show(truncate = false)
+-----------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|image_name       |result                                                                                                                                                                                        |
+-----------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|palace.JPEG      |[ The image depicts a large, ornate room with high ceilings and beautifully decorated walls. There are several chairs placed throughout the space, some of which have cushions]               |
|egyptian_cat.jpeg|[ The image features two cats lying on a pink surface, possibly a bed or sofa. One cat is positioned towards the left side of the scene and appears to be sleeping while holding]             |
|hippopotamus.JPEG|[ A large brown hippo is swimming in a body of water, possibly an aquarium. The hippo appears to be enjoying its time in the water and seems relaxed as it floats]                            |
|hen.JPEG         |[ The image features a large chicken standing next to several baby chickens. In total, there are five birds in the scene: one adult and four young ones. They appear to be gathered together] |
|ostrich.JPEG     |[ The image features a large, long-necked bird standing in the grass. It appears to be an ostrich or similar species with its head held high and looking around. In addition to]              |
|junco.JPEG       |[ A small bird with a black head and white chest is standing on the snow. It appears to be looking at something, possibly food or another animal in its vicinity. The scene takes place out]  |
|bluetick.jpg     |[ A dog with a red collar is sitting on the floor, looking at something. The dog appears to be staring into the distance or focusing its attention on an object in front of it.]              |
|chihuahua.jpg    |[ A small brown dog wearing a sweater is sitting on the floor. The dog appears to be looking at something, possibly its owner or another animal in the room. It seems comfortable and relaxed]|
|tractor.JPEG     |[ A man is sitting in the driver's seat of a green tractor, which has yellow wheels and tires. The tractor appears to be parked on top of an empty field with]                                |
|ox.JPEG          |[ A large bull with horns is standing in a grassy field.]                                                                                                                                     |
+-----------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
Linear Supertypes
HasProtectedParams, HasLlamaCppInferenceProperties, HasLlamaCppModelProperties, HasEngine, HasBatchedAnnotateTextImage[AutoGGUFVisionModel], AnnotatorModel[AutoGGUFVisionModel], CanBeLazy, RawAnnotator[AutoGGUFVisionModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[AutoGGUFVisionModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. AutoGGUFVisionModel
  2. HasProtectedParams
  3. HasLlamaCppInferenceProperties
  4. HasLlamaCppModelProperties
  5. HasEngine
  6. HasBatchedAnnotateTextImage
  7. AnnotatorModel
  8. CanBeLazy
  9. RawAnnotator
  10. HasOutputAnnotationCol
  11. HasInputAnnotationCols
  12. HasOutputAnnotatorType
  13. ParamsAndFeaturesWritable
  14. HasFeatures
  15. DefaultParamsWritable
  16. MLWritable
  17. Model
  18. Transformer
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AutoGGUFVisionModel()

    Annotator reference id.

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

  2. new AutoGGUFVisionModel(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. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  12. def batchAnnotate(batchedAnnotations: Seq[(Annotation, AnnotationImage)]): Seq[Seq[Annotation]]

    Completes the batch of annotations.

    Completes the batch of annotations.

    batchedAnnotations

    The single batch of annotations

    returns

    Completed text sequences sentences that belong to the same original row !! (challenging)

    Definition Classes
    AutoGGUFVisionModel → HasBatchedAnnotateTextImage
  13. def batchProcess(rows: Iterator[_]): Iterator[Row]
    Definition Classes
    HasBatchedAnnotateTextImage
  14. val batchSize: IntParam

    Size of every batch (Default depends on model).

    Size of every batch (Default depends on model).

    Definition Classes
    HasBatchedAnnotateTextImage
  15. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  16. val cachePrompt: BooleanParam

    Definition Classes
    HasLlamaCppInferenceProperties
  17. val chatTemplate: Param[String]

    Definition Classes
    HasLlamaCppModelProperties
  18. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  19. final def clear(param: Param[_]): AutoGGUFVisionModel.this.type
    Definition Classes
    Params
  20. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  21. def copy(extra: ParamMap): AutoGGUFVisionModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  22. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  23. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  24. val defragmentationThreshold: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  25. val disableTokenIds: IntArrayParam

    Definition Classes
    HasLlamaCppInferenceProperties
  26. val dynamicTemperatureExponent: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  27. val dynamicTemperatureRange: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  28. val embedding: BooleanParam

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

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  36. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  37. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  38. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  39. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  40. val flashAttention: BooleanParam

    Definition Classes
    HasLlamaCppModelProperties
  41. val frequencyPenalty: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  42. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  44. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  45. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  46. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  47. def getBatchSize: Int

    Size of every batch.

    Size of every batch.

    Definition Classes
    HasBatchedAnnotateTextImage
  48. def getCachePrompt: Boolean

    Definition Classes
    HasLlamaCppInferenceProperties
  49. def getChatTemplate: String

    Definition Classes
    HasLlamaCppModelProperties
  50. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  51. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  52. def getDefragmentationThreshold: Float

    Definition Classes
    HasLlamaCppModelProperties
  53. def getDisableTokenIds: Array[Int]

    Definition Classes
    HasLlamaCppInferenceProperties
  54. def getDynamicTemperatureExponent: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  55. def getDynamicTemperatureRange: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  56. def getEmbedding: Boolean

    Definition Classes
    HasLlamaCppModelProperties
  57. def getEngine: String

    Definition Classes
    HasEngine
  58. def getFlashAttention: Boolean

    Definition Classes
    HasLlamaCppModelProperties
  59. def getFrequencyPenalty: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  60. def getGrammar: String

    Definition Classes
    HasLlamaCppInferenceProperties
  61. def getIgnoreEos: Boolean

    Definition Classes
    HasLlamaCppInferenceProperties
  62. def getInferenceParameters: InferenceParameters
    Attributes
    protected
    Definition Classes
    HasLlamaCppInferenceProperties
  63. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  64. def getInputPrefix: String

    Definition Classes
    HasLlamaCppInferenceProperties
  65. def getInputSuffix: String

    Definition Classes
    HasLlamaCppInferenceProperties
  66. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  67. def getMainGpu: Int

    Definition Classes
    HasLlamaCppModelProperties
  68. def getMetadata: String

    Get the metadata for the model

    Get the metadata for the model

    Definition Classes
    HasLlamaCppModelProperties
  69. def getMetadataMap: Map[String, Map[String, String]]
    Definition Classes
    HasLlamaCppModelProperties
  70. def getMinKeep: Int

    Definition Classes
    HasLlamaCppInferenceProperties
  71. def getMinP: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  72. def getMiroStat: String

    Definition Classes
    HasLlamaCppInferenceProperties
  73. def getMiroStatEta: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  74. def getMiroStatTau: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  75. def getModelDraft: String

    Definition Classes
    HasLlamaCppModelProperties
  76. def getModelIfNotSet: GGUFWrapperMultiModal

  77. def getModelParameters: ModelParameters
    Attributes
    protected
    Definition Classes
    HasLlamaCppModelProperties
  78. def getNBatch: Int

    Definition Classes
    HasLlamaCppModelProperties
  79. def getNCtx: Int

    Definition Classes
    HasLlamaCppModelProperties
  80. def getNDraft: Int

    Definition Classes
    HasLlamaCppModelProperties
  81. def getNGpuLayers: Int

    Definition Classes
    HasLlamaCppModelProperties
  82. def getNGpuLayersDraft: Int

    Definition Classes
    HasLlamaCppModelProperties
  83. def getNKeep: Int

    Definition Classes
    HasLlamaCppInferenceProperties
  84. def getNPredict: Int
    Definition Classes
    HasLlamaCppInferenceProperties
  85. def getNProbs: Int

    Definition Classes
    HasLlamaCppInferenceProperties
  86. def getNThreads: Int

    Definition Classes
    HasLlamaCppModelProperties
  87. def getNThreadsBatch: Int

    Definition Classes
    HasLlamaCppModelProperties
  88. def getNUbatch: Int

    Definition Classes
    HasLlamaCppModelProperties
  89. def getNoKvOffload: Boolean

    Definition Classes
    HasLlamaCppModelProperties
  90. def getNuma: String

    Definition Classes
    HasLlamaCppModelProperties
  91. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  92. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  93. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  94. def getPenalizeNl: Boolean

    Definition Classes
    HasLlamaCppInferenceProperties
  95. def getPenaltyPrompt: String

    Definition Classes
    HasLlamaCppInferenceProperties
  96. def getPoolingType: String

    Definition Classes
    HasLlamaCppModelProperties
  97. def getPresencePenalty: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  98. def getRepeatLastN: Int

    Definition Classes
    HasLlamaCppInferenceProperties
  99. def getRepeatPenalty: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  100. def getRopeFreqBase: Float

    Definition Classes
    HasLlamaCppModelProperties
  101. def getRopeFreqScale: Float

    Definition Classes
    HasLlamaCppModelProperties
  102. def getRopeScalingType: String

    Definition Classes
    HasLlamaCppModelProperties
  103. def getSamplers: Array[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  104. def getSeed: Int

    Definition Classes
    HasLlamaCppInferenceProperties
  105. def getSplitMode: String

    Definition Classes
    HasLlamaCppModelProperties
  106. def getStopStrings: Array[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  107. def getSystemPrompt: String

    Definition Classes
    HasLlamaCppModelProperties
  108. def getTemperature: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  109. def getTfsZ: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  110. def getTokenBias: Map[String, Float]

    Definition Classes
    HasLlamaCppInferenceProperties
  111. def getTokenIdBias: Map[Int, Float]

    Definition Classes
    HasLlamaCppInferenceProperties
  112. def getTopK: Int

    Definition Classes
    HasLlamaCppInferenceProperties
  113. def getTopP: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  114. def getTypicalP: Float

    Definition Classes
    HasLlamaCppInferenceProperties
  115. def getUseChatTemplate: Boolean

    Definition Classes
    HasLlamaCppInferenceProperties
  116. def getUseMlock: Boolean

    Definition Classes
    HasLlamaCppModelProperties
  117. def getUseMmap: Boolean

    Definition Classes
    HasLlamaCppModelProperties
  118. def getYarnAttnFactor: Float

    Definition Classes
    HasLlamaCppModelProperties
  119. def getYarnBetaFast: Float

    Definition Classes
    HasLlamaCppModelProperties
  120. def getYarnBetaSlow: Float

    Definition Classes
    HasLlamaCppModelProperties
  121. def getYarnExtFactor: Float

    Definition Classes
    HasLlamaCppModelProperties
  122. def getYarnOrigCtx: Int

    Definition Classes
    HasLlamaCppModelProperties
  123. 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
    Definition Classes
    HasLlamaCppModelProperties
  124. val grammar: Param[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  125. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  126. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  127. def hasParent: Boolean
    Definition Classes
    Model
  128. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  129. val ignoreEos: BooleanParam

    Definition Classes
    HasLlamaCppInferenceProperties
  130. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  131. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  132. val inputAnnotatorTypes: Array[AnnotatorType]

    Annotator reference id.

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

    Definition Classes
    AutoGGUFVisionModel → HasInputAnnotationCols
  133. 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
  134. val inputPrefix: Param[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  135. val inputSuffix: Param[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  136. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  137. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  138. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  139. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  140. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  141. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  142. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  143. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  144. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  145. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  146. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  147. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  148. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  149. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  150. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  151. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  152. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  153. val logger: Logger
    Attributes
    protected
    Definition Classes
    HasLlamaCppModelProperties
  154. val mainGpu: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  155. val metadata: ProtectedParam[String]
    Definition Classes
    HasLlamaCppModelProperties
  156. val minKeep: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  157. val minP: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  158. val miroStat: Param[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  159. val miroStatEta: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  160. val miroStatTau: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  161. val modelDraft: Param[String]

    Definition Classes
    HasLlamaCppModelProperties
  162. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  163. val nBatch: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  164. val nCtx: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  165. val nDraft: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  166. val nGpuLayers: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  167. val nGpuLayersDraft: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  168. val nKeep: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  169. val nPredict: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  170. val nProbs: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  171. val nThreads: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  172. val nThreadsBatch: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  173. val nUbatch: IntParam

    Definition Classes
    HasLlamaCppModelProperties
  174. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  175. val noKvOffload: BooleanParam

    Definition Classes
    HasLlamaCppModelProperties
  176. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  177. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  178. 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
    Definition Classes
    HasLlamaCppModelProperties
  179. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    AutoGGUFVisionModel → ParamsAndFeaturesWritable
  180. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  181. val outputAnnotatorType: AnnotatorType
    Definition Classes
    AutoGGUFVisionModel → HasOutputAnnotatorType
  182. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  183. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  184. var parent: Estimator[AutoGGUFVisionModel]
    Definition Classes
    Model
  185. val penalizeNl: BooleanParam

    Definition Classes
    HasLlamaCppInferenceProperties
  186. val penaltyPrompt: Param[String]

    Definition Classes
    HasLlamaCppInferenceProperties
  187. 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
    Definition Classes
    HasLlamaCppModelProperties
  188. val presencePenalty: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  189. val repeatLastN: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  190. val repeatPenalty: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  191. val ropeFreqBase: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  192. val ropeFreqScale: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  193. 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
    Definition Classes
    HasLlamaCppModelProperties
  194. val samplers: StringArrayParam

    Definition Classes
    HasLlamaCppInferenceProperties
  195. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  196. val seed: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  197. def set[T](param: ProtectedParam[T], value: T): AutoGGUFVisionModel.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
  198. def set[T](feature: StructFeature[T], value: T): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  199. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  200. def set[T](feature: SetFeature[T], value: Set[T]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  201. def set[T](feature: ArrayFeature[T], value: Array[T]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  202. final def set(paramPair: ParamPair[_]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  203. final def set(param: String, value: Any): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  204. final def set[T](param: Param[T], value: T): AutoGGUFVisionModel.this.type
    Definition Classes
    Params
  205. def setBatchSize(size: Int): AutoGGUFVisionModel.this.type

    Size of every batch.

    Size of every batch.

    Definition Classes
    HasBatchedAnnotateTextImage
  206. def setCachePrompt(cachePrompt: Boolean): AutoGGUFVisionModel.this.type

    Whether to remember the prompt to avoid reprocessing it

    Whether to remember the prompt to avoid reprocessing it

    Definition Classes
    HasLlamaCppInferenceProperties
  207. def setChatTemplate(chatTemplate: String): AutoGGUFVisionModel.this.type

    The chat template to use

    The chat template to use

    Definition Classes
    HasLlamaCppModelProperties
  208. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  209. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  210. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  211. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  212. final def setDefault(paramPairs: ParamPair[_]*): AutoGGUFVisionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  213. final def setDefault[T](param: Param[T], value: T): AutoGGUFVisionModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  214. def setDefragmentationThreshold(defragThold: Float): AutoGGUFVisionModel.this.type

    Set the KV cache defragmentation threshold

    Set the KV cache defragmentation threshold

    Definition Classes
    HasLlamaCppModelProperties
  215. def setDisableTokenIds(disableTokenIds: Array[Int]): AutoGGUFVisionModel.this.type

    Set the token ids to disable in the completion.

    Set the token ids to disable in the completion. This corresponds to setTokenBias with a value of Float.NEGATIVE_INFINITY.

    Definition Classes
    HasLlamaCppInferenceProperties
  216. def setDynamicTemperatureExponent(dynatempExponent: Float): AutoGGUFVisionModel.this.type

    Set the dynamic temperature exponent

    Set the dynamic temperature exponent

    Definition Classes
    HasLlamaCppInferenceProperties
  217. def setDynamicTemperatureRange(dynatempRange: Float): AutoGGUFVisionModel.this.type

    Set the dynamic temperature range

    Set the dynamic temperature range

    Definition Classes
    HasLlamaCppInferenceProperties
  218. def setEmbedding(embedding: Boolean): AutoGGUFVisionModel.this.type

    Whether to load model with embedding support

    Whether to load model with embedding support

    Definition Classes
    HasLlamaCppModelProperties
  219. def setFlashAttention(flashAttention: Boolean): AutoGGUFVisionModel.this.type

    Whether to enable Flash Attention

    Whether to enable Flash Attention

    Definition Classes
    HasLlamaCppModelProperties
  220. def setFrequencyPenalty(frequencyPenalty: Float): AutoGGUFVisionModel.this.type

    Set the repetition alpha frequency penalty

    Set the repetition alpha frequency penalty

    Definition Classes
    HasLlamaCppInferenceProperties
  221. def setGpuSplitMode(splitMode: String): AutoGGUFVisionModel.this.type

    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
    Definition Classes
    HasLlamaCppModelProperties
  222. def setGrammar(grammar: String): AutoGGUFVisionModel.this.type

    Set BNF-like grammar to constrain generations

    Set BNF-like grammar to constrain generations

    Definition Classes
    HasLlamaCppInferenceProperties
  223. def setIgnoreEos(ignoreEos: Boolean): AutoGGUFVisionModel.this.type

    Set whether to ignore end of stream token and continue generating (implies --logit-bias 2-inf)

    Set whether to ignore end of stream token and continue generating (implies --logit-bias 2-inf)

    Definition Classes
    HasLlamaCppInferenceProperties
  224. final def setInputCols(value: String*): AutoGGUFVisionModel.this.type
    Definition Classes
    HasInputAnnotationCols
  225. def setInputCols(value: Array[String]): AutoGGUFVisionModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  226. def setInputPrefix(inputPrefix: String): AutoGGUFVisionModel.this.type

    Set the prompt to start generation with

    Set the prompt to start generation with

    Definition Classes
    HasLlamaCppInferenceProperties
  227. def setInputSuffix(inputSuffix: String): AutoGGUFVisionModel.this.type

    Set a suffix for infilling

    Set a suffix for infilling

    Definition Classes
    HasLlamaCppInferenceProperties
  228. def setLazyAnnotator(value: Boolean): AutoGGUFVisionModel.this.type
    Definition Classes
    CanBeLazy
  229. def setMainGpu(mainGpu: Int): AutoGGUFVisionModel.this.type

    Set the GPU that is used for scratch and small tensors

    Set the GPU that is used for scratch and small tensors

    Definition Classes
    HasLlamaCppModelProperties
  230. def setMetadata(metadata: String): AutoGGUFVisionModel.this.type

    Set the metadata for the model

    Set the metadata for the model

    Definition Classes
    HasLlamaCppModelProperties
  231. def setMinKeep(minKeep: Int): AutoGGUFVisionModel.this.type

    Set the amount of tokens the samplers should return at least (0 = disabled)

    Set the amount of tokens the samplers should return at least (0 = disabled)

    Definition Classes
    HasLlamaCppInferenceProperties
  232. def setMinP(minP: Float): AutoGGUFVisionModel.this.type

    Set min-p sampling

    Set min-p sampling

    Definition Classes
    HasLlamaCppInferenceProperties
  233. def setMiroStat(mirostat: String): AutoGGUFVisionModel.this.type

    Set MiroStat sampling strategies.

    Set MiroStat sampling strategies.

    • DISABLED: No MiroStat
    • V1: MiroStat V1
    • V2: MiroStat V2
    Definition Classes
    HasLlamaCppInferenceProperties
  234. def setMiroStatEta(mirostatEta: Float): AutoGGUFVisionModel.this.type

    Set the MiroStat learning rate, parameter eta

    Set the MiroStat learning rate, parameter eta

    Definition Classes
    HasLlamaCppInferenceProperties
  235. def setMiroStatTau(mirostatTau: Float): AutoGGUFVisionModel.this.type

    Set the MiroStat target entropy, parameter tau

    Set the MiroStat target entropy, parameter tau

    Definition Classes
    HasLlamaCppInferenceProperties
  236. def setModelDraft(modelDraft: String): AutoGGUFVisionModel.this.type

    Set the draft model for speculative decoding

    Set the draft model for speculative decoding

    Definition Classes
    HasLlamaCppModelProperties
  237. def setModelIfNotSet(spark: SparkSession, wrapper: GGUFWrapperMultiModal): AutoGGUFVisionModel.this.type

  238. def setNBatch(nBatch: Int): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  239. def setNCtx(nCtx: Int): AutoGGUFVisionModel.this.type

    Set the size of the prompt context

    Set the size of the prompt context

    Definition Classes
    HasLlamaCppModelProperties
  240. def setNDraft(nDraft: Int): AutoGGUFVisionModel.this.type

    Set the number of tokens to draft for speculative decoding

    Set the number of tokens to draft for speculative decoding

    Definition Classes
    HasLlamaCppModelProperties
  241. def setNGpuLayers(nGpuLayers: Int): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  242. def setNGpuLayersDraft(nGpuLayersDraft: Int): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  243. def setNKeep(nKeep: Int): AutoGGUFVisionModel.this.type

    Set the number of tokens to keep from the initial prompt

    Set the number of tokens to keep from the initial prompt

    Definition Classes
    HasLlamaCppInferenceProperties
  244. def setNParallel(nParallel: Int): AutoGGUFVisionModel.this.type

    Sets the number of parallel processes for decoding.

    Sets the number of parallel processes for decoding. This is an alias for setBatchSize.

    nParallel

    The number of parallel processes for decoding

  245. def setNPredict(nPredict: Int): AutoGGUFVisionModel.this.type

    Set the number of tokens to predict

    Set the number of tokens to predict

    Definition Classes
    HasLlamaCppInferenceProperties
  246. def setNProbs(nProbs: Int): AutoGGUFVisionModel.this.type

    Set the amount top tokens probabilities to output if greater than 0.

    Set the amount top tokens probabilities to output if greater than 0.

    Definition Classes
    HasLlamaCppInferenceProperties
  247. def setNThreads(nThreads: Int): AutoGGUFVisionModel.this.type

    Set the number of threads to use during generation

    Set the number of threads to use during generation

    Definition Classes
    HasLlamaCppModelProperties
  248. def setNThreadsBatch(nThreadsBatch: Int): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  249. def setNUbatch(nUbatch: Int): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  250. def setNoKvOffload(noKvOffload: Boolean): AutoGGUFVisionModel.this.type

    Whether to disable KV offload

    Whether to disable KV offload

    Definition Classes
    HasLlamaCppModelProperties
  251. def setNumaStrategy(numa: String): AutoGGUFVisionModel.this.type

    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
    Definition Classes
    HasLlamaCppModelProperties
  252. final def setOutputCol(value: String): AutoGGUFVisionModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  253. def setParent(parent: Estimator[AutoGGUFVisionModel]): AutoGGUFVisionModel
    Definition Classes
    Model
  254. def setPenalizeNl(penalizeNl: Boolean): AutoGGUFVisionModel.this.type

    Set whether to penalize newline tokens

    Set whether to penalize newline tokens

    Definition Classes
    HasLlamaCppInferenceProperties
  255. def setPenaltyPrompt(penaltyPrompt: String): AutoGGUFVisionModel.this.type

    Override which part of the prompt is penalized for repetition.

    Override which part of the prompt is penalized for repetition.

    Definition Classes
    HasLlamaCppInferenceProperties
  256. def setPoolingType(poolingType: String): AutoGGUFVisionModel.this.type

    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
    Definition Classes
    HasLlamaCppModelProperties
  257. def setPresencePenalty(presencePenalty: Float): AutoGGUFVisionModel.this.type

    Set the repetition alpha presence penalty

    Set the repetition alpha presence penalty

    Definition Classes
    HasLlamaCppInferenceProperties
  258. def setRepeatLastN(repeatLastN: Int): AutoGGUFVisionModel.this.type

    Set the last n tokens to consider for penalties

    Set the last n tokens to consider for penalties

    Definition Classes
    HasLlamaCppInferenceProperties
  259. def setRepeatPenalty(repeatPenalty: Float): AutoGGUFVisionModel.this.type

    Set the penalty of repeated sequences of tokens

    Set the penalty of repeated sequences of tokens

    Definition Classes
    HasLlamaCppInferenceProperties
  260. def setRopeFreqBase(ropeFreqBase: Float): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  261. def setRopeFreqScale(ropeFreqScale: Float): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  262. def setRopeScalingType(ropeScalingType: String): AutoGGUFVisionModel.this.type

    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
    Definition Classes
    HasLlamaCppModelProperties
  263. def setSamplers(samplers: Array[String]): AutoGGUFVisionModel.this.type

    Set which samplers to use for token generation in the given order .

    Set which samplers to use for token generation in the given order .

    Available Samplers are:

    • TOP_K: Top-k sampling
    • TFS_Z: Tail free sampling
    • TYPICAL_P: Locally typical sampling p
    • TOP_P: Top-p sampling
    • MIN_P: Min-p sampling
    • TEMPERATURE: Temperature sampling
    Definition Classes
    HasLlamaCppInferenceProperties
  264. def setSeed(seed: Int): AutoGGUFVisionModel.this.type

    Set the RNG seed

    Set the RNG seed

    Definition Classes
    HasLlamaCppInferenceProperties
  265. def setStopStrings(stopStrings: Array[String]): AutoGGUFVisionModel.this.type

    Set strings upon seeing which token generation is stopped

    Set strings upon seeing which token generation is stopped

    Definition Classes
    HasLlamaCppInferenceProperties
  266. def setSystemPrompt(systemPrompt: String): AutoGGUFVisionModel.this.type

    Set a system prompt to use

    Set a system prompt to use

    Definition Classes
    HasLlamaCppModelProperties
  267. def setTemperature(temperature: Float): AutoGGUFVisionModel.this.type

    Set the temperature

    Set the temperature

    Definition Classes
    HasLlamaCppInferenceProperties
  268. def setTfsZ(tfsZ: Float): AutoGGUFVisionModel.this.type

    Set tail free sampling, parameter z

    Set tail free sampling, parameter z

    Definition Classes
    HasLlamaCppInferenceProperties
  269. def setTokenBias(tokenBias: HashMap[String, Double]): AutoGGUFVisionModel.this.type

    Set the tokens to disable during completion.

    Set the tokens to disable during completion. (Override for PySpark)

    Definition Classes
    HasLlamaCppInferenceProperties
  270. def setTokenBias(tokenBias: Map[String, Float]): AutoGGUFVisionModel.this.type

    Set the tokens to disable during completion.

    Set the tokens to disable during completion.

    Definition Classes
    HasLlamaCppInferenceProperties
  271. def setTokenIdBias(tokenIdBias: HashMap[Integer, Double]): AutoGGUFVisionModel.this.type

    Set the token ids to disable in the completion.

    Set the token ids to disable in the completion. (Override for PySpark)

    Definition Classes
    HasLlamaCppInferenceProperties
  272. def setTokenIdBias(tokenIdBias: Map[Int, Float]): AutoGGUFVisionModel.this.type

    Set the token ids to disable in the completion.

    Set the token ids to disable in the completion.

    Definition Classes
    HasLlamaCppInferenceProperties
  273. def setTopK(topK: Int): AutoGGUFVisionModel.this.type

    Set top-k sampling

    Set top-k sampling

    Definition Classes
    HasLlamaCppInferenceProperties
  274. def setTopP(topP: Float): AutoGGUFVisionModel.this.type

    Set top-p sampling

    Set top-p sampling

    Definition Classes
    HasLlamaCppInferenceProperties
  275. def setTypicalP(typicalP: Float): AutoGGUFVisionModel.this.type

    Set locally typical sampling, parameter p

    Set locally typical sampling, parameter p

    Definition Classes
    HasLlamaCppInferenceProperties
  276. def setUseChatTemplate(useChatTemplate: Boolean): AutoGGUFVisionModel.this.type

    Set whether or not generate should apply a chat template

    Set whether or not generate should apply a chat template

    Definition Classes
    HasLlamaCppInferenceProperties
  277. def setUseMlock(useMlock: Boolean): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  278. def setUseMmap(useMmap: Boolean): AutoGGUFVisionModel.this.type

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

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

    Definition Classes
    HasLlamaCppModelProperties
  279. def setYarnAttnFactor(yarnAttnFactor: Float): AutoGGUFVisionModel.this.type

    Set the YaRN scale sqrt(t) or attention magnitude

    Set the YaRN scale sqrt(t) or attention magnitude

    Definition Classes
    HasLlamaCppModelProperties
  280. def setYarnBetaFast(yarnBetaFast: Float): AutoGGUFVisionModel.this.type

    Set the YaRN low correction dim or beta

    Set the YaRN low correction dim or beta

    Definition Classes
    HasLlamaCppModelProperties
  281. def setYarnBetaSlow(yarnBetaSlow: Float): AutoGGUFVisionModel.this.type

    Set the YaRN high correction dim or alpha

    Set the YaRN high correction dim or alpha

    Definition Classes
    HasLlamaCppModelProperties
  282. def setYarnExtFactor(yarnExtFactor: Float): AutoGGUFVisionModel.this.type

    Set the YaRN extrapolation mix factor

    Set the YaRN extrapolation mix factor

    Definition Classes
    HasLlamaCppModelProperties
  283. def setYarnOrigCtx(yarnOrigCtx: Int): AutoGGUFVisionModel.this.type

    Set the YaRN original context size of model

    Set the YaRN original context size of model

    Definition Classes
    HasLlamaCppModelProperties
  284. val stopStrings: StringArrayParam

    Definition Classes
    HasLlamaCppInferenceProperties
  285. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  286. val systemPrompt: Param[String]

    Definition Classes
    HasLlamaCppModelProperties
  287. val temperature: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  288. val tfsZ: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  289. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  290. val tokenBias: StructFeature[Map[String, Float]]

    Definition Classes
    HasLlamaCppInferenceProperties
  291. val tokenIdBias: StructFeature[Map[Int, Float]]
    Definition Classes
    HasLlamaCppInferenceProperties
  292. val topK: IntParam

    Definition Classes
    HasLlamaCppInferenceProperties
  293. val topP: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  294. 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
  295. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  296. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  297. 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
  298. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  299. val typicalP: FloatParam

    Definition Classes
    HasLlamaCppInferenceProperties
  300. val uid: String
    Definition Classes
    AutoGGUFVisionModel → Identifiable
  301. val useChatTemplate: BooleanParam

    Definition Classes
    HasLlamaCppInferenceProperties
  302. val useMlock: BooleanParam

    Definition Classes
    HasLlamaCppModelProperties
  303. val useMmap: BooleanParam

    Definition Classes
    HasLlamaCppModelProperties
  304. 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
  305. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  306. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  307. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  308. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  309. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  310. val yarnAttnFactor: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  311. val yarnBetaFast: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  312. val yarnBetaSlow: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  313. val yarnExtFactor: FloatParam

    Definition Classes
    HasLlamaCppModelProperties
  314. val yarnOrigCtx: IntParam

    Definition Classes
    HasLlamaCppModelProperties

Inherited from HasProtectedParams

Inherited from HasLlamaCppInferenceProperties

Inherited from HasLlamaCppModelProperties

Inherited from HasEngine

Inherited from HasBatchedAnnotateTextImage[AutoGGUFVisionModel]

Inherited from AnnotatorModel[AutoGGUFVisionModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[AutoGGUFVisionModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[AutoGGUFVisionModel]

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.

Members

Parameter setters

Parameter getters