Design a project-specific harness with specialist agents, task Skills and a working orchestration structure.
Explore skills
Original workflows for websites, images, presentations, and everything in motion.
Collect execution feedback and improve an existing harness, its agents, Skills and orchestration rules.
Build and debug Python agents and multi-agent workflows with Swarms tools, memory and orchestration architectures.
Field-tested methodology and concrete recipes for training and operating large-scale LLM/VLM/multi-modal models end to end - choosing and benchmarking accelerators, storage and network; SLURM/Kubernetes orchestration; maximizing training throughput and fitting models in memory; diagnosing and surviving training instabilities, NaN/Inf, and hardware/job failures; checkpointing and fault tolerance; inference…
A small library, made with care. More skills are on the way.