Agent skill · NVIDIA
tao-run-on-docker
Docker conventions for running NVIDIA GPU container workloads — NGC authentication, --gpus flag, mount patterns,
What it needs
About 8k tokens when loaded.
What this skill does
Docker for NVIDIA GPU Workloads Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery). This skill documents the generic Docker conventions that GPU container workloads rely on. Model and data skills specify what image and what command to run; this skill covers how to run docker in a way that satisfies GPU + NVIDIA container requirements. Sources: official Docker CLI reference (<https://docs.docker.com/reference/cli/docker/>) and NVIDIA Container Toolkit docs. Prerequisites 1. Host GPU runtime — by default, NVIDIA driver >=580, CUDA Toolkit >=13.0, and NVIDIA Container Toolkit >=1.19.0. If the selected model's references/skillinfo.yaml declares runtimerequirements.gpuhost, pass those values to tao-setup-nvidia-gpu-host instead. Model requirements override the defaults for that workflow. 2. Docker — docker --version must return ≥ 20.10. Install: <https://docs.docker.com/engine/install/>. 3. NGC API key for nvcr.io/ pulls. Get from <https://ngc.nvidia.com/>. If the selected model declares runtimerequirements.gpuhost, append the corresponding --min-driver-version, --min-cuda-version, and --min-container-toolkit-version values to both the check and any approved install command. Do not apply one model's override to unrelated workflows. NGC authentication Persists in ~/.docker/config.json across reboots. Re-run on unauthorized errors. docker run — canonical flags Notes: --gpus '"device=0,1"' — specific GPUs (double-quote-escaped). Without nvidia-container-toolkit: could not select device driver "" with capabilities: [[gpu]]. --rm — clean up the container at exit; omit when you want docker logs after exit. --shm-size=8g — torchrun + PyTorch DataLoaders exhaust the default 64 MB /dev/shm otherwise; size it for multi-GPU training and raise (e.g. 16g) if you still hit Bus error. --user "$(id -u):$(id -g)" — required by default whenever a bind mount is writable. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/tao-run-on-docker