Individual skill
spark-environment-setup
Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.
plugins/dgx-spark-ops/skills/spark-environment-setup/SKILL.md
Source commit 4bde3168b43c0655c4d00ea2726e631719908a6d
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- Last checked
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- Nov 9, 2026
- License
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SKILL.mdcore · 8,113 bytesSKILL.mdcore · 8,113 bytesSKILL.mdcore · 8,113 bytesSKILL.mdcore · 8,113 bytesSKILL.mdcore · 8,113 bytesSKILL.mdcore · 8,113 bytesreferences/container-workflow.mddoc · 4,171 bytesreferences/stack-matrix.mddoc · 7,064 bytes
Read excerpt
# Spark Environment Setup
DGX Spark ships a GB10 Grace Blackwell chip: aarch64 CPU, SM121
GPU, 128GB unified memory, CUDA 13. This is a narrower and
younger platform than a standard x86 CUDA 12 box, so package
selection and ABI matching matter more than usual — the wheel
ecosystem for aarch64 + CUDA 13 is still filling in.
## When to Use This Skill
- Setting up a fresh Spark box for training or inference.
- Hitting an import error mentioning `libcudart`, a missing
symbol, or a wheel that "installed fine but won't load."
- A framework install (PyTorch, Unsloth, TRL, vLLM, xformers)