fine tuning

Operating AI across different clouds and execution engines becomes complex and difficult to maintain with cloud native tools as the number of different integrations between systems proliferates at scale. OpenShiftAI provides a cohesive hybrid, multi-cloud AI platform that enables enterprises to separate concerns between pipeline orchestration and workload execution reducing complexity in the data and governance subdomains and enabling enterprises to operate AI at scale.

Fine-tuning of a large language model (LLM) can be peformed using QLoRA (Quantized Low Rank Adapters) and PEFT (Parameter-Efficient Fine-Tuning) techniques. PEFT (Parameter-Efficient Fine-Tuning): PEFT is a technique for fine-tuning large language models with a small number of additional parameters, known as adapters, while freezing the original model parameters.