#[non_exhaustive]pub struct ModelSpeculativeDecodingConfigBuilder { /* private fields */ }Expand description
A builder for ModelSpeculativeDecodingConfig.
Implementations§
Source§impl ModelSpeculativeDecodingConfigBuilder
impl ModelSpeculativeDecodingConfigBuilder
Sourcepub fn technique(self, input: ModelSpeculativeDecodingTechnique) -> Self
pub fn technique(self, input: ModelSpeculativeDecodingTechnique) -> Self
The speculative decoding technique to apply during model optimization.
This field is required.Sourcepub fn set_technique(
self,
input: Option<ModelSpeculativeDecodingTechnique>,
) -> Self
pub fn set_technique( self, input: Option<ModelSpeculativeDecodingTechnique>, ) -> Self
The speculative decoding technique to apply during model optimization.
Sourcepub fn get_technique(&self) -> &Option<ModelSpeculativeDecodingTechnique>
pub fn get_technique(&self) -> &Option<ModelSpeculativeDecodingTechnique>
The speculative decoding technique to apply during model optimization.
Sourcepub fn training_data_source(
self,
input: ModelSpeculativeDecodingTrainingDataSource,
) -> Self
pub fn training_data_source( self, input: ModelSpeculativeDecodingTrainingDataSource, ) -> Self
The location of the training data to use for speculative decoding. The data must be formatted as ShareGPT, OpenAI Completions or OpenAI Chat Completions. The input can also be unencrypted captured data from a SageMaker endpoint as long as the endpoint uses one of the above formats.
Sourcepub fn set_training_data_source(
self,
input: Option<ModelSpeculativeDecodingTrainingDataSource>,
) -> Self
pub fn set_training_data_source( self, input: Option<ModelSpeculativeDecodingTrainingDataSource>, ) -> Self
The location of the training data to use for speculative decoding. The data must be formatted as ShareGPT, OpenAI Completions or OpenAI Chat Completions. The input can also be unencrypted captured data from a SageMaker endpoint as long as the endpoint uses one of the above formats.
Sourcepub fn get_training_data_source(
&self,
) -> &Option<ModelSpeculativeDecodingTrainingDataSource>
pub fn get_training_data_source( &self, ) -> &Option<ModelSpeculativeDecodingTrainingDataSource>
The location of the training data to use for speculative decoding. The data must be formatted as ShareGPT, OpenAI Completions or OpenAI Chat Completions. The input can also be unencrypted captured data from a SageMaker endpoint as long as the endpoint uses one of the above formats.
Sourcepub fn build(self) -> ModelSpeculativeDecodingConfig
pub fn build(self) -> ModelSpeculativeDecodingConfig
Consumes the builder and constructs a ModelSpeculativeDecodingConfig.
Trait Implementations§
Source§impl Clone for ModelSpeculativeDecodingConfigBuilder
impl Clone for ModelSpeculativeDecodingConfigBuilder
Source§fn clone(&self) -> ModelSpeculativeDecodingConfigBuilder
fn clone(&self) -> ModelSpeculativeDecodingConfigBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl Default for ModelSpeculativeDecodingConfigBuilder
impl Default for ModelSpeculativeDecodingConfigBuilder
Source§fn default() -> ModelSpeculativeDecodingConfigBuilder
fn default() -> ModelSpeculativeDecodingConfigBuilder
Source§impl PartialEq for ModelSpeculativeDecodingConfigBuilder
impl PartialEq for ModelSpeculativeDecodingConfigBuilder
Source§fn eq(&self, other: &ModelSpeculativeDecodingConfigBuilder) -> bool
fn eq(&self, other: &ModelSpeculativeDecodingConfigBuilder) -> bool
self and other values to be equal, and is used by ==.impl StructuralPartialEq for ModelSpeculativeDecodingConfigBuilder
Auto Trait Implementations§
impl Freeze for ModelSpeculativeDecodingConfigBuilder
impl RefUnwindSafe for ModelSpeculativeDecodingConfigBuilder
impl Send for ModelSpeculativeDecodingConfigBuilder
impl Sync for ModelSpeculativeDecodingConfigBuilder
impl Unpin for ModelSpeculativeDecodingConfigBuilder
impl UnwindSafe for ModelSpeculativeDecodingConfigBuilder
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