Nebullvm

Covers inference, infrastructure, and fine-tuning in one collection, addressing multiple pain points in AI deployment pipelines, as highlighted by tools like Speedster, Nos, and ChatLLaMA.

Speedster applies state-of-the-art optimization techniques tailored to GPUs and CPUs, potentially reducing inference costs through efficient hardware coupling.

Nos maximizes GPU utilization in Kubernetes clusters via real-time dynamic partitioning, helping manage infrastructure costs for scalable AI workloads.

Explicitly targets reducing inference, infrastructure, and data costs through specialized tools, offering a practical approach to AI optimization.