executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
generation-inferenceRoute Pyramid-Flow generation workflows, Gradio demos, notebook recipes, and multi-GPU inference launchers.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when the user asks how to run, adapt, validate, or troubleshoot Pyramid-Flow generation and demo workflows.
data-preparation.training-workflows.PyramidDiTForVideoGeneration internals, scheduler details, VAE internals, tensor-shape contracts, or reusable component APIs: use core-components.image_path, and Gradio/Hugging Face cache issues.scripts/check_generation_prereqs.py validates checkpoint layout, model/variant compatibility, image-to-video inputs, CUDA/MPS visibility, and sequence-parallel GPU counts without importing the side-effectful demo apps.scripts/run_generation.py is a safe-by-default command planner and optional execution wrapper distilled from the repository launchers. By default it prints the command that would run; pass --execute or --launch only when a real checkpoint, importable Pyramid-Flow package, and required backend are ready.pyramid_flux/pyramid_mmdit, 384p/768p, and image-variant combinations before launching.torchrun + world_size == sp_group_size; sequence parallelism is not a CPU/MPS fallback.