Rust Ml
- Machine learning and numerical computing in Rust — tensors, framework choice (candle/burn/tch/ort/linfa), dtypes and determinism, avoiding needless copies of large tensors, GPU management, and serving a model without blocking the async runtime. Use for inference or training, loading a model (safetensors/ONNX), tokenizing, a data pipeline (polars/arrow), or deploying behind an API. Triggers: candle, burn, tch, ort, ONNX, ndarray, polars, safetensors, inference, GPU, spawnblocking.
Works with: Claude Code (native) · Cursor, Codex CLI (manual)
native: this artifact type is that client's own format
Install (Claude Code):
cp -r rust-ml ~/.claude/skills/- Adoption: 1 repos
- Upkeep: 100.0
- Freshness: 99.0
- Evidence coverage: 84% of the inputs this score can use — the rest are unknown, and the score is discounted for it
- Health: active
- Contributors: 4
Security audit
Not scanned yet. We audit npm-published capabilities for known advisories, install-time scripts and permission surface; this one has no npm package we can resolve, or has not reached the queue.
source ↗ · skill:gurinderu/rust-ml
Already running this? npx tashan-cli doctor checks your whole config against the Index — how it works ›
Measured 2026-08-09 · scorer s5 · how · something wrong here?