Creating a New Custom Model in Generative AI

 Important



Pre-General Availability: 2023-09-18

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In the navigation bar of the Console, choose a region that hosts Generative AI, for example, US Midwest (Chicago). If you don't know which region to choose, see Regions with Generative AI.
Open the navigation menu and click Analytics & AI. Under AI Services, click Generative AI.
In the left navigation, choose a compartment for the custom model.
 Important

Ensure that you have the following permissions:
Permission to manage generative-ai-family in this compartment
The proper permission to object-family based on your role:
To add training datasets to Object Storage buckets or to delete or replace the training datasets, you need permission to manage object-family in the bucket's compartment. You assign these training datasets to custom models when you create the models.
When you create a custom model, to list and choose a training dataset that you or someone else added to Object Storage, you need permission to use object-family in the bucket's compartment. If you have permission to manage object-family, you don't need this use permission.
Click Custom models.
Click Create model.
Click Create a new model.
Select a compartment to create the model 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 for the custom model. If you leave the name blank, the system generates a name that you can change later.

The generated name has the format generativeaimodel<timestamp>.

For example: generativeaimodel20230902013055

(Optional) Enter a version and description. If you leave the version blank, the version remains blank and you can add a version later.
Click Next.
For Base Model, click an available text generation pretrained model to fine-tune:
cohere.command-light.14.2
For the base model size and maximum tokens, see the text generation pretrained models.
Choose a dedicated fine-tuning AI cluster by performing one of the following actions:
Click a Dedicated AI cluster from the drop-down list.
 Note

Only active, fine-tuning dedicated AI clusters are listed in the dedicated AI cluster drop-down list. If you just created a fine-tuning dedicated AI cluster, wait a few minutes for that cluster to become active.
Click Create new dedicated AI cluster and perform the following steps:
(Optional) Enter a name and description. If you leave the name blank, the system generates a name with the generativeaidedicatedaicluster<timestamp> format, that you can change later.
For Type, click Fine-tuning-beta.
(Required) Read the terms and click to agree with the beta testing use of the dedicated AI cluster.
Click Create.
Wait a few minutes for the cluster to be created.
From the Dedicated AI cluster drop-down list, click the dedicated AI cluster that you created.
Click Next.
Click the name of the bucket that contains the training file for fine-tuning the base model.
If you can't find the bucket that contains the training file, follow these steps:
The bucket that you're looking for might be in another compartment. Click Change compartment and choose the compartment that hosts the bucket with the training data.
You might have permissions for creating a custom model, but not for listing the bucket and its contents. Ask an administrator to give you permission to buckets and objects in that compartment.
Click the name of the training file to use for fine-tuning the base model.
Preview how the data in the training file is ingested. If the data records parse correctly, click Submit. Otherwise, fix the data and then create a custom model. See Training Data Requirements.
After the model is created, you can get the custom model's details from the detail page.