技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
nebullvm-backends【数据与研究】Guides NebullVM data/device handling, backend selection, compiler lists, and optional dependency troubleshooting.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when the user is asking about the lower-level NebullVM support layer behind Speedster: data shapes, device parsing, backend lists, optional dependencies, or compiler selection.
DataManager input formats and dataloader conversion.check_device, gpu_is_available, TPU fallback, or AWS Neuron fallback behavior.references/api-reference.md for the verified enums, dataclasses, and selector functions.references/data-and-devices.md for the accepted data and device formats.references/compiler-selection.md for the framework/backend/compiler decision logic.references/troubleshooting.md for compiler, platform, and optional dependency failures.scripts/nebullvm_backend_probe.py for a safe selector/device/import smoke probe.../speedster-optimization/SKILL.md when the question is about the higher-level optimization API rather than the support layer.nebullvm.core.models.DataManager and PytorchDataset behavior.auto_installer.If the user is trying to understand which framework/backend/compiler combination is valid, start here. If they are already calling optimize_model, read the Speedster sub-skill first.