Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationSpec
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationSpec
- 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
-
#base_teacher_model ⇒ String
The base teacher model that is being distilled, e.g., "gemini-1.0-pro-002".
-
#hyper_parameters ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationHyperParameters
Hyperparameters for Distillation.
-
#pipeline_root_directory ⇒ String
Required.
-
#student_model ⇒ String
The student model that is being tuned, e.g., "google/gemma-2b-1.1-it".
-
#training_dataset_uri ⇒ String
Required.
-
#tuned_teacher_model_source ⇒ String
The resource name of the Tuned teacher model.
-
#validation_dataset_uri ⇒ String
Optional.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1DistillationSpec
constructor
A new instance of GoogleCloudAiplatformV1beta1DistillationSpec.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1DistillationSpec
Returns a new instance of GoogleCloudAiplatformV1beta1DistillationSpec.
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 7024 def initialize(**args) update!(**args) end |
Instance Attribute Details
#base_teacher_model ⇒ String
The base teacher model that is being distilled, e.g., "gemini-1.0-pro-002".
Corresponds to the JSON property baseTeacherModel
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 6987 def base_teacher_model @base_teacher_model end |
#hyper_parameters ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationHyperParameters
Hyperparameters for Distillation.
Corresponds to the JSON property hyperParameters
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 6992 def hyper_parameters @hyper_parameters end |
#pipeline_root_directory ⇒ String
Required. 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
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 6999 def pipeline_root_directory @pipeline_root_directory end |
#student_model ⇒ String
The student model that is being tuned, e.g., "google/gemma-2b-1.1-it".
Corresponds to the JSON property studentModel
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 7004 def student_model @student_model end |
#training_dataset_uri ⇒ String
Required. 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
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 7010 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`
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 7016 def tuned_teacher_model_source @tuned_teacher_model_source 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
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 7022 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 7029 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) @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) @validation_dataset_uri = args[:validation_dataset_uri] if args.key?(:validation_dataset_uri) end |