Generally Available: Model fine-tuning support for Kubernetes AI Toolchain Operator (KAITO)

With parameter-efficient fine-tuning (PEFT) support, you can now customize pre-trained models from the KAITO repository to your data and use cases directly in your cluster, while maintaining the data compliance rules for your organization. 

Simply choose a target model, select one of the various tuning methods, point to retraining data and where to store fine-tuning results in your KAITO tuning workspace. This allows you to serve your “smarter” model and simplify ML lifecycle management directly from the AKS cluster.

Learn more:

• Fine-tuning API documentation
• New models supported in KAITO repository