What problem does it solve? Configuring distributed training job launches across interactive torchrun sessions, Slurm HPC clusters, and SkyPilot cloud environments requires knowing the correct YAML fields, rendezvous settings, and profiling options, which are easy to get wrong. ## Core Features & Use Cases - Slurm Configuration: Generate slurm: YAML blocks with nodes, ntasks_per_node, time, account/partition, container_image, mounts, and env_vars, with automatic WORLD_SIZE, MASTER_ADDR, and MASTER_PORT handling. - SkyPilot Cloud Launches: Configure cloud-agnostic jobs with accelerators, spot instances, disk size, region, and setup commands, including spot preemption checkpointing guidance. - Nsight Systems Profiling: Enable nsys_enabled: true on Slurm jobs to produce .nsys-rep reports for diagnostic performance analysis. - Use Case: A user needs to launch a two-node finetuning job with 8 GPUs per node on Slurm; the skill provides the exact YAML section and explains distributed environment setup. ## Quick Start Ask how to configure a Slurm or SkyPilot launch for a NeMo AutoModel training job and receive the correct YAML configuration. ## Quick Start Ask how to configure a two-node Slurm finetuning job with 8 GPUs per node and get the complete slurm YAML section.