Selecting a Fine-Tuning Method in Generative AI
When you create a custom model, OCI Generative AI fine-tunes the pretrained base models using a method that matches the base model.
Important
Some OCI Generative AI foundational pretrained base models supported for the dedicated serving mode are now deprecated and will retire no sooner than 6 months after the release of the 1st replacement model. You can host a base model, or fine-tune a base model and host the fine-tuned model on a dedicated AI cluster (dedicated serving mode) until the base model is retired. For dedicated serving mode retirement dates, see Retiring the Models.
Some OCI Generative AI foundational pretrained base models supported for the dedicated serving mode are now deprecated and will retire no sooner than 6 months after the release of the 1st replacement model. You can host a base model, or fine-tune a base model and host the fine-tuned model on a dedicated AI cluster (dedicated serving mode) until the base model is retired. For dedicated serving mode retirement dates, see Retiring the Models.
The following table lists the method that Generative AI uses to train each type of base model:
| Pretrained Base Models | Training Method |
|---|---|
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Note
For information about the hyperparameters used for each training method, see Fine-Tuning Hyperparameters in Generative AI.
For information about the hyperparameters used for each training method, see Fine-Tuning Hyperparameters in Generative AI.