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Mechanism
Breaks down how the skill works and what it produces, so you can quickly judge whether it fits your scenario and value.
When setting up ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13), hitting libcudart or wheel-ABI errors, or choosing between NGC containers and bare pip.
--no-deps for Unsloth to avoid ABI conflicts.torch.version.cuda.A working, ABI-matched ML environment on DGX Spark with verified GPU visibility, avoiding common import/segfault failures.
Use Cases
A researcher receives a fresh DGX Spark and needs to run Unsloth fine-tuning. They use this skill to pick the Unsloth container, pin its digest, and verify GPU via torch. This avoids aarch64/CUDA13 ABI mismatches and saves hours of broken pip installs, delivering a reproducible training base.
An engineer sees `ImportError: undefined symbol` after pip install on Spark. They apply the ABI rule, check `torch.version.cuda` shows 12 not 13, then switch to cu130 wheels or NGC container. The skill resolves the segfault quickly without blind reinstalls, restoring working inference.
Skill Relationships
Dependency relationships read as "the upper tier points to the lower tier." The current Skill sits in the middle tier — above are Skills that depend on it, below are Skills it depends on.
Tier 1 · These Skills Use Me
Tier 2 · Current Skill
Tier 3 · I Use These Skills
Browse this skill's relationships within its skillset. Click a node to switch the side panel; use the search box to jump to any skill.
Skill File