Automate ML model benchmarking across versions and languages with JSON and Markdown reports.
npx skills add https://github.com/jiunbae/agent-skills --skill ml-benchmark
Please help me install this Agent Skill. Skill: ml-benchmark Source: https://github.com/jiunbae/agent-skills/tree/main/ml/ml-benchmark Command: npx skills add https://github.com/jiunbae/agent-skills --skill ml-benchmark
ML 모델의 성능 벤치마크를 자동으로 실행하고, 여러 버전 간의 성능 차이를 한 눈에 비교해 의사결정을 빠르게 돕습니다.
예: "langdetector 벤치마크 100회 돌려줘"
High-intent search queries and answers about installing and using this skill.
ML model benchmarking automates performance measurement across multiple versions, languages, and scenarios to capture latency (P50/P95/P99), throughput, GPU memory, and accuracy metrics. Use the provided Bash script with YAML profiles and CLI commands (run, evaluate, compare, history) to execute benchmarks and generate JSON/Markdown comparative reports.
Yes. The benchmarking workflow measures latency, throughput, GPU memory, and accuracy across multiple models simultaneously, then generates comparative reports in JSON and Markdown formats to highlight performance differences and support rapid decision-making.
You need Python, numpy, pandas, and matplotlib installed. These prerequisites enable the Bash script and CLI commands to execute benchmarks, process metrics data, and generate visualization outputs for performance comparison.
Use YAML profile configurations to define benchmark scenarios. These profiles standardize test parameters across runs, enabling you to measure latency, throughput, and GPU memory consistently and generate reproducible comparative reports.
Yes. The benchmarking tool operates across multiple models, versions, and languages to measure performance metrics uniformly, allowing you to compare latency, throughput, and accuracy results across different language implementations.
The benchmarking workflow generates JSON and Markdown outputs. JSON formats enable programmatic result processing, while Markdown reports provide human-readable performance comparisons for stakeholder communication and decision-making.
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