Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationSpec

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

Tuning Spec for Distillation.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1DistillationSpec

Returns a new instance of GoogleCloudAiplatformV1beta1DistillationSpec.



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17292

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#base_teacher_model ⇒ String

The base teacher model that is being distilled. See Supported models. Corresponds to the JSON property baseTeacherModel

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17242

def base_teacher_model
  @base_teacher_model
end

#hyper_parameters ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationHyperParameters

Hyperparameters for Distillation. Corresponds to the JSON property hyperParameters

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17247

def hyper_parameters
  @hyper_parameters
end

#pipeline_root_directory ⇒ String

Deprecated. A path in a Cloud Storage bucket, which will be treated as the root output directory of the distillation pipeline. It is used by the system to generate the paths of output artifacts. Corresponds to the JSON property pipelineRootDirectory

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17254

def pipeline_root_directory
  @pipeline_root_directory
end

#prompt_dataset_uri ⇒ String

Optional. Cloud Storage path to file containing prompt dataset for distillation. The dataset must be formatted as a JSONL file. Corresponds to the JSON property promptDatasetUri

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17260

def prompt_dataset_uri
  @prompt_dataset_uri
end

#student_model ⇒ String

The student model that is being tuned, e.g., "google/gemma-2b-1.1-it". Deprecated. Use base_model instead. Corresponds to the JSON property studentModel

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17266

def student_model
  @student_model
end

#training_dataset_uri ⇒ String

Deprecated. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file. Corresponds to the JSON property trainingDatasetUri

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17272

def training_dataset_uri
  @training_dataset_uri
end

#tuned_teacher_model_source ⇒ String

The resource name of the Tuned teacher model. Format: projects/project/ locations/location/models/model`. Corresponds to the JSON propertytunedTeacherModelSource`

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17278

def tuned_teacher_model_source
  @tuned_teacher_model_source
end

#tuning_mode ⇒ String

Optional. Specifies the tuning mode for distillation (sft part). This feature is only available for open source models. Corresponds to the JSON property tuningMode

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17284

def tuning_mode
  @tuning_mode
end

#validation_dataset_uri ⇒ String

Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file. Corresponds to the JSON property validationDatasetUri

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17290

def validation_dataset_uri
  @validation_dataset_uri
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 17297

def update!(**args)
  @base_teacher_model = args[:base_teacher_model] if args.key?(:base_teacher_model)
  @hyper_parameters = args[:hyper_parameters] if args.key?(:hyper_parameters)
  @pipeline_root_directory = args[:pipeline_root_directory] if args.key?(:pipeline_root_directory)
  @prompt_dataset_uri = args[:prompt_dataset_uri] if args.key?(:prompt_dataset_uri)
  @student_model = args[:student_model] if args.key?(:student_model)
  @training_dataset_uri = args[:training_dataset_uri] if args.key?(:training_dataset_uri)
  @tuned_teacher_model_source = args[:tuned_teacher_model_source] if args.key?(:tuned_teacher_model_source)
  @tuning_mode = args[:tuning_mode] if args.key?(:tuning_mode)
  @validation_dataset_uri = args[:validation_dataset_uri] if args.key?(:validation_dataset_uri)
end