Oracle Cloud Infrastructure Documentation

Creating a Dedicated AI Cluster in Generative AI for Fine-Tuning Custom Models

Create a dedicated AI cluster resource in OCI Generative AI to use for fine-tuning custom models.

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.
  1. In the navigation bar of the Console, select a region with Generative AI, for example, US Midwest (Chicago) or UK South (London). See which models are offered in your region.
  2. Open the navigation menu and click Analytics & AI. Under AI Services, click Generative AI.
  3. Select a compartment that you have permission to work in.
  4. Click Dedicated AI clusters.
  5. Click Create dedicated AI cluster.
  6. Select a compartment to create the dedicated AI cluster in. The default compartment is the one you selected in step 3, but you can select any compartment that you have permission to work in.
  7. (Optional) Enter a name and description for the cluster. If you don't enter a name, the system generates one that you can change later.

    The generated name has the format generativeaidedicatedaicluster<timestamp>.

    For example: generativeaidedicatedaicluster20240601202357

  8. For Cluster type, select Fine-tuning.
  9. For Base model, select the base model for the custom model that you want to fine-tune on this cluster:

    Chat

    • cohere.command-r-08-2024 - Provisions 8 Small Cohere V2 units.
    • cohere.command-r-16k - Provisions 8 Small Cohere V2 units.
    • meta.llama-3.1-70b-instruct - Provisions 2 Large Generic units.
    • meta.llama-3-70b-instruct - Provisions 2 Large Generic units. (This model is deprecated.)

    Generation

    Important

    The number of units in a fine-tuning cluster is preset and depends on the base model selected for fine-tuning. Fine-tuning clusters need more resources than hosting clusters because they use more GPUs. You can fine-tune several models on the same cluster, as long as the custom models train on the same base model.
  10. Read the commitment unit hours for the fine-tuning cluster and select the checkbox to agree to the commitment.
  11. (Optional) Click Show advanced options and assign tags to this dedicated AI cluster.
  12. Click Create.
    Note

    Fine-tuning clusters take some time to create. After a fine-tuning cluster is in an active state, you can use it to fine-tune custom models. You can select a cluster for fine-tuning when you create a custom model.
After the dedicated AI cluster is created, you can get the cluster's details.