L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

environment-and-model-setup

environment-and-model-setup

Set up and verify Hunyuan3D-2 Python, CUDA, extension, and model-cache environments.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: environment-and-model-setup description: "Set up and verify Hunyuan3D-2 Python, CUDA, extension, and model-cache environments." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

Hunyuan3D-2 Environment and Model Setup

Use this sub-skill when the task is about installing hy3dgen, choosing PyTorch/CUDA variants, building texture extensions, validating GPU/backend readiness, selecting model subfolders, or planning local/offline model caches.

Route here for

  • Installing package requirements and hy3dgen from a package source or a repository tree the user is intentionally working in.
  • Building custom_rasterizer and mesh_processor for texture generation.
  • Diagnosing CUDA toolkit/header, PyTorch CUDA, pymeshlab/OpenGL, and extension import failures.
  • Understanding model zoo names, subfolders, VRAM needs, and HY3DGEN_MODELS cache behavior.
  • Running non-downloading environment checks before shape/texture/service workflows.

Do not route here for

  • Shape generation code parameters after the environment is ready: use ../shape-generation/.
  • Texture/mesh workflow details after extensions are ready: use ../texture-and-mesh/.
  • API server/Gradio/Blender client behavior: use ../services-and-integrations/.

Essential references

  • Installation and backends for installation order, CUDA extension build guidance, and backend readiness checks.
  • Model overview for model repo/subfolder selection, VRAM guidance, and cache behavior.
  • Troubleshooting for common install/backend failures and stale documentation warnings.

Bundled helper

  • scripts/check_install.py checks package metadata/imports and optional CUDA/extension readiness without downloading model weights.

Examples:

python scripts/check_install.py --json
python scripts/check_install.py --check-cuda --json
python scripts/check_install.py --check-cuda --check-extensions --json

A passing helper check proves installation/backend readiness for the selected probes. It does not prove that full model inference ran or that model checkpoints are cached.

Skills enregistrées