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.
- 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.
- Open the navigation menu and click Analytics & AI. Under AI Services, click Generative AI.
- Select a compartment that you have permission to work in.
- Click Dedicated AI clusters.
- Click Create dedicated AI cluster.
- 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.
- (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 - For Cluster type, select Fine-tuning.
-
For Base model, select the base model for the custom
model that you want to fine-tune on this cluster:
- Llama-3-70b-instruct - Provisions two Large Generic units.
- Cohere.command - Provisions two Large Cohere units.
- Cohere.command-light - Provisions two Small Cohere units.
Important
When you create a cluster for fine-tuning, two units are created for the base model that you select. Hosting a model requires at least one unit and fine-tuning requires two units, because fine-tuning a model requires more GPUs than hosting a model. The number of units for fine-tuning is hard-coded to two and you can't change it. You can use the same fine-tuning cluster to fine-tune several models as long as they use the same base model - Read the commitment unit hours for the fine-tuning cluster and select the checkbox to agree to the commitment.
- (Optional) Click Show advanced options and assign tags to this dedicated AI cluster.
-
Click Create.
Note
Clusters for fine-tuning take some time to create. After the cluster is in an active state, you can use it to fine-tune custom models. To use a cluster for fine-tuning, select that cluster when you create a custom model.