FineTuningJob

Struct FineTuningJob 

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pub struct FineTuningJob {
Show 19 fields pub id: String, pub created_at: i64, pub error: Option<FineTuningJobError>, pub fine_tuned_model: Option<String>, pub finished_at: Option<i64>, pub hyperparameters: Option<FineTuningJobHyperparameters>, pub model: String, pub object: String, pub organization_id: String, pub result_files: Vec<String>, pub status: String, pub trained_tokens: Option<i64>, pub training_file: String, pub validation_file: Option<String>, pub integrations: Option<Vec<FineTuningIntegration>>, pub seed: i32, pub estimated_finish: Option<i64>, pub method: Option<FineTuneMethod>, pub metadata: Option<Metadata>,
}
Expand description

The fine_tuning.job object represents a fine-tuning job that has been created through the API.

§Used By

  • /fine_tuning/jobs (GET - in ListPaginatedFineTuningJobsResponse, POST response)
  • /fine_tuning/jobs/{fine_tuning_job_id} (GET, POST response)
  • /fine_tuning/jobs/{fine_tuning_job_id}/cancel (POST response)
  • FineTuningJobCheckpoint

Fields§

§id: String

The object identifier, which can be referenced in the API endpoints.

§created_at: i64

The Unix timestamp (in seconds) for when the fine-tuning job was created.

§error: Option<FineTuningJobError>

For fine-tuning jobs that have failed, this will contain more information on the cause of the failure.

§fine_tuned_model: Option<String>

The name of the fine-tuned model that is being created. Null if the job is still running.

§finished_at: Option<i64>

The Unix timestamp (in seconds) for when the fine-tuning job was finished. Null if the job is still running.

§hyperparameters: Option<FineTuningJobHyperparameters>
👎Deprecated: Use method.hyperparameters instead

Deprecated : The hyperparameters used for the fine-tuning job. See method.

§model: String

The base model that is being fine-tuned.

§object: String

The object type, which is always “fine_tuning.job”.

§organization_id: String

The organization that owns the fine-tuning job.

§result_files: Vec<String>

The compiled results file ID(s) for the fine-tuning job.

§status: String

The current status of the fine-tuning job.

§trained_tokens: Option<i64>

The total number of billable tokens processed by this job. Null if the job is still running.

§training_file: String

The file ID used for training.

§validation_file: Option<String>

The file ID used for validation. Null if no validation file was provided.

§integrations: Option<Vec<FineTuningIntegration>>

A list of integrations to enable for this fine-tuning job.

§seed: i32

The seed used for the fine-tuning job.

§estimated_finish: Option<i64>

The Unix timestamp (in seconds) for when the job is estimated to finish. Null if not running.

§method: Option<FineTuneMethod>

The fine-tuning method used.

§metadata: Option<Metadata>

Set of 16 key-value pairs attached to the object.

Trait Implementations§

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impl Clone for FineTuningJob

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fn clone(&self) -> FineTuningJob

Returns a duplicate of the value. Read more
1.0.0 · Source§

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

Performs copy-assignment from source. Read more
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impl Debug for FineTuningJob

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

Formats the value using the given formatter. Read more
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impl<'de> Deserialize<'de> for FineTuningJob

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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl PartialEq for FineTuningJob

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fn eq(&self, other: &FineTuningJob) -> bool

Tests for self and other values to be equal, and is used by ==.
1.0.0 · Source§

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl Serialize for FineTuningJob

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

Serialize this value into the given Serde serializer. Read more
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impl StructuralPartialEq for FineTuningJob

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🔬This is a nightly-only experimental API. (clone_to_uninit)
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