Manage Customization Jobs
Use customization jobs to fine-tune a model using a dataset and hyperparameters.
How It Works
A customization job references a Model Entity that contains the base model checkpoint, and is submitted to one of two backends — automodel (default, multi-GPU) or unsloth (single-GPU, quantized). The job then runs on the platform’s GPU cluster. When training completes:
- LoRA jobs: Create an Adapter attached to the original Model Entity. Adapters can be auto-deployed to NIMs.
- Full fine-tuning jobs: Create a new Model Entity with the customized weights, linked to the base model.
This design keeps adapters organized with their parent models and simplifies deployment workflows.
Submission is backend-specific (you submit to the automodel or unsloth backend), but every job runs on the shared platform Jobs service. As a result, you poll status, list, and cancel jobs through that service the same way regardless of which backend you used.
Prerequisites
Before you can customize a model using a customization job, make sure that you have prepared and uploaded a dataset to the dataset repository.
Task Guides
Perform common customization job tasks.
The value for NMP_BASE_URL will depend on your deployment. After the standard Setup flow, the default local URL is http://localhost:8080. Otherwise, consult with your cluster administrator.
Create a customization job using SFT or Knowledge Distillation.
Check the status of a customization job.
List all active customization jobs to find a job name for use with Get Status or Cancel.
Cancel a customization job using its name and workspace.
References
Refer to the following pages for more information on customization jobs.