trait FineTuning extends AnyRef
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- abstract def cancelFineTuningJob(fine_tuning_job_id: String): ZIO[Any, OpenAIFailure, FineTuningJob]
Immediately cancel a fine-tune job.
Immediately cancel a fine-tune job.
- fine_tuning_job_id
The ID of the fine-tuning job to cancel.
- abstract def createFineTuningJob(body: CreateFineTuningJobRequest): ZIO[Any, OpenAIFailure, FineTuningJob]
Creates a job that fine-tunes a specified model from a given dataset.
Creates a job that fine-tunes a specified model from a given dataset.
Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.
[Learn more about fine-tuning](/docs/guides/fine-tuning)
- abstract def listFineTuningEvents(fine_tuning_job_id: String, after: Optional[String], limit: Optional[Int]): ZIO[Any, OpenAIFailure, ListFineTuningJobEventsResponse]
Get status updates for a fine-tuning job.
Get status updates for a fine-tuning job.
- fine_tuning_job_id
The ID of the fine-tuning job to get events for.
- after
Identifier for the last event from the previous pagination request.
- limit
Number of events to retrieve.
- abstract def listPaginatedFineTuningJobs(after: Optional[String], limit: Optional[Int]): ZIO[Any, OpenAIFailure, ListPaginatedFineTuningJobsResponse]
List your organization's fine-tuning jobs
List your organization's fine-tuning jobs
- after
Identifier for the last job from the previous pagination request.
- limit
Number of fine-tuning jobs to retrieve.
- abstract def retrieveFineTuningJob(fine_tuning_job_id: String): ZIO[Any, OpenAIFailure, FineTuningJob]
Get info about a fine-tuning job.
Get info about a fine-tuning job.
[Learn more about fine-tuning](/docs/guides/fine-tuning)
- fine_tuning_job_id
The ID of the fine-tuning job.
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- def createFineTuningJob(model: Model, trainingFile: String, hyperparameters: Optional[Hyperparameters] = Optional.Absent, suffix: Optional[Suffix] = Optional.Absent, validationFile: Optional[String] = Optional.Absent): ZIO[Any, OpenAIFailure, FineTuningJob]
Creates a job that fine-tunes a specified model from a given dataset.
Creates a job that fine-tunes a specified model from a given dataset.
Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.
[Learn more about fine-tuning](/docs/guides/fine-tuning)
- model
The name of the model to fine-tune. You can select one of the [supported models](/docs/guides/fine-tuning/what-models-can-be-fine-tuned).
- trainingFile
The ID of an uploaded file that contains training data. See [upload file](/docs/api-reference/files/upload) 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. See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.- hyperparameters
The hyperparameters used for the fine-tuning job.
- suffix
A string of up to 18 characters that will be added to your fine-tuned model name. For example, a
suffixof "custom-model-name" would produce a model name likeft:gpt-3.5-turbo:openai:custom-model-name:7p4lURel.- validationFile
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](/docs/guides/fine-tuning) for more details.
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