pub struct CreateFineTuningJobRequestArgs { /* private fields */ }
Expand description
Builder for CreateFineTuningJobRequest
.
Implementations§
Source§impl CreateFineTuningJobRequestArgs
impl CreateFineTuningJobRequestArgs
Sourcepub fn model<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn model<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
The name of the model to fine-tune. You can select one of the supported models.
Sourcepub fn training_file<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn training_file<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
The ID of an uploaded file that contains training data.
See upload file for how to upload a file.
Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose fine-tune
.
The contents of the file should differ depending on if the model uses the chat, completions format, or if the fine-tuning method uses the preference format.
See the fine-tuning guide for more details.
Sourcepub fn hyperparameters<VALUE: Into<Hyperparameters>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn hyperparameters<VALUE: Into<Hyperparameters>>( &mut self, value: VALUE, ) -> &mut Self
The hyperparameters used for the fine-tuning job.
This value is now deprecated in favor of method
, and should be passed in under the method
parameter.
Sourcepub fn suffix<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn suffix<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
A string of up to 64 characters that will be added to your fine-tuned model name.
For example, a suffix
of “custom-model-name” would produce a model name like ft:gpt-4o-mini:openai:custom-model-name:7p4lURel
.
Sourcepub fn validation_file<VALUE: Into<String>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn validation_file<VALUE: Into<String>>( &mut self, value: VALUE, ) -> &mut Self
The ID of an uploaded file that contains validation data.
If you provide this file, the data is used to generate validation metrics periodically during fine-tuning. These metrics can be viewed in the fine-tuning results file. The same data should not be present in both train and validation files.
Your dataset must be formatted as a JSONL file. You must upload your file with the purpose fine-tune
.
See the fine-tuning guide for more details.
Sourcepub fn integrations<VALUE: Into<Vec<FineTuningIntegration>>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn integrations<VALUE: Into<Vec<FineTuningIntegration>>>( &mut self, value: VALUE, ) -> &mut Self
A list of integrations to enable for your fine-tuning job.
Sourcepub fn seed<VALUE: Into<u32>>(&mut self, value: VALUE) -> &mut Self
pub fn seed<VALUE: Into<u32>>(&mut self, value: VALUE) -> &mut Self
The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases. If a seed is not specified, one will be generated for you.
pub fn method<VALUE: Into<FineTuneMethod>>(&mut self, value: VALUE) -> &mut Self
Sourcepub fn build(&self) -> Result<CreateFineTuningJobRequest, OpenAIError>
pub fn build(&self) -> Result<CreateFineTuningJobRequest, OpenAIError>
Trait Implementations§
Source§impl Clone for CreateFineTuningJobRequestArgs
impl Clone for CreateFineTuningJobRequestArgs
Source§fn clone(&self) -> CreateFineTuningJobRequestArgs
fn clone(&self) -> CreateFineTuningJobRequestArgs
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
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