Struct CreateTuningJobConfig 

pub struct CreateTuningJobConfig {

    pub http_options: Option<HttpOptions>,
    pub method: Option<TuningMethod>,
    pub validation_dataset: Option<TuningValidationDataset>,
    pub tuned_model_display_name: Option<String>,
    pub description: Option<String>,
    pub epoch_count: Option<i32>,
    pub learning_rate_multiplier: Option<f32>,
    pub export_last_checkpoint_only: Option<bool>,
    pub pre_tuned_model_checkpoint_id: Option<String>,
    pub adapter_size: Option<AdapterSize>,
    pub tuning_mode: Option<TuningMode>,
    pub custom_base_model: Option<String>,
    pub batch_size: Option<i32>,
    pub learning_rate: Option<f32>,
    pub evaluation_config: Option<EvaluationConfig>,
    pub encryption_spec: Option<EncryptionSpec>,
    pub labels: Option<HashMap<String, String>>,
    pub beta: Option<f32>,
    pub base_teacher_model: Option<String>,
    pub tuned_teacher_model_source: Option<String>,
    pub sft_loss_weight_multiplier: Option<f32>,
    pub output_uri: Option<String>,
}

Fine-tuning job creation request - optional fields.

Fields

http_options: Option<HttpOptions>

Optional. HTTP request overrides (SDK only, not sent to API).

method: Option<TuningMethod>

validation_dataset: Option<TuningValidationDataset>

tuned_model_display_name: Option<String>

description: Option<String>

epoch_count: Option<i32>

learning_rate_multiplier: Option<f32>

export_last_checkpoint_only: Option<bool>

pre_tuned_model_checkpoint_id: Option<String>

adapter_size: Option<AdapterSize>

tuning_mode: Option<TuningMode>

Optional. Tuning mode for SFT tuning (Vertex AI only).

custom_base_model: Option<String>

Optional. Custom base model for tuning (Vertex AI OSS models only).

batch_size: Option<i32>

learning_rate: Option<f32>

evaluation_config: Option<EvaluationConfig>

encryption_spec: Option<EncryptionSpec>

Optional. Customer-managed encryption key options for a TuningJob.

labels: Option<HashMap<String, String>>

beta: Option<f32>

base_teacher_model: Option<String>

Optional. The base teacher model that is being distilled (Distillation only).

tuned_teacher_model_source: Option<String>

Optional. The resource name of the tuned teacher model (Distillation only).

sft_loss_weight_multiplier: Option<f32>

Optional. Multiplier for adjusting the weight of the SFT loss (Distillation only).

output_uri: Option<String>

Optional. The Cloud Storage location where the tuning job outputs are written (Vertex AI only).

Trait Implementations

impl Clone for CreateTuningJobConfig

fn clone(&self) -> CreateTuningJobConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateTuningJobConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for CreateTuningJobConfig

fn default() -> CreateTuningJobConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for CreateTuningJobConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for CreateTuningJobConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.