cosmos3-setup
bởi nvidia
Hướng dẫn người dùng qua quá trình cài đặt Cosmos3, thiết lập môi trường, tải xuống checkpoint và xác minh. Sử dụng khi người dùng hỏi "cách cài đặt cosmos3", "cách…
npx skills add https://github.com/nvidia/cosmos-framework --skill cosmos3-setupCosmos3 Setup
When to use this skill
- Use when a user wants to install Cosmos3 or set up a development environment
- Use when a user asks about system requirements, CUDA versions, or GPU compatibility
- Use when a user needs to download model checkpoints or configure HuggingFace auth
- Use when a user wants to run Cosmos3 inside a Docker container or NGC container
- For errors during setup, hand off to the cosmos3-env-troubleshoot skill
Path convention
All paths below are relative to the cosmos3 package root (../../../ from this skill file). All uv run / python commands should also be run from there.
Where to find answers
The canonical setup reference is docs/setup.md. The README (README.md § Setup) has the shortest quickstart.
| User question | Go to |
|---|---|
| What are the system requirements? | docs/setup.md § System Requirements |
| How do I install with uv? (sync, pip venv, pip system) | docs/setup.md § Virtual Environment |
| How do I install with Docker? | docs/setup.md § Docker Container |
| Custom torch/CUDA versions or attention backends? | docs/setup.md § Advanced |
| Which CUDA version? (cu130 vs cu128) | docs/setup.md § CUDA Variants, docs/faq.md § Which CUDA version? |
| How do I download checkpoints? | docs/setup.md § Downloading Base Checkpoints |
| NGC container issues? | docs/setup.md § PyTorch Import Issue |
| Any installation error | ../cosmos3-env-troubleshoot/SKILL.md |
Setup steps at a glance
- Clone the repository and
cdinto the project root (the directory containingpyproject.toml) - System deps:
sudo apt-get install -y --no-install-recommends curl ffmpeg git-lfs libx11-dev tree wget - Install uv:
curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env - Install package:
uv sync --all-extras --group=cu130-train && source .venv/bin/activate && export LD_LIBRARY_PATH=(usecu128-trainon older drivers; the inference-onlycu130/cu128groups omit the training extras) - Checkpoints: auto-downloaded during inference; requires HuggingFace auth (see docs)
- Verify:
uv run --all-extras --group=cu130-train python -c "import cosmos_framework; print('ok')"
Things not obvious from the docs
- NGC container caveat: you must run
export LD_LIBRARY_PATH=''before any Python imports when inside an NGC PyTorch container. Easy to miss. - CUDA version alignment: the major CUDA version from
nvidia-smimust matchtorch.version.cuda. Mismatches cause cryptic shared-library errors. HF_HOME: controls where checkpoints are cached (default:~/.cache/huggingface). Set this if disk space is tight or you want a shared cache.- Conflicting env vars: stale
HF_TOKENorHUGGING_FACE_HUB_TOKENenv vars can silently override CLI auth. Check withprintenv | grep HF_.
Related skills
| Skill | When to use |
|---|---|
../cosmos3-inference/SKILL.md | Running inference after setup is complete |
../cosmos3-codebase-nav/SKILL.md | Finding files, parameters, and configs in code |
../cosmos3-env-troubleshoot/SKILL.md | Debugging environment and runtime errors |