Benchmark Thai word segmentation across kham-core, nlpo3, and PyThaiNLP.
npx skills add https://github.com/preedep/kham --skill benchmark-runner-preedep
Please help me install this Agent Skill. Skill: benchmark-runner Source: https://github.com/preedep/kham/tree/main/.claude/skills/benchmark-runner Command: npx skills add https://github.com/preedep/kham --skill benchmark-runner-preedep
Benchmarks Thai word segmentation performance across multiple toolchains to help developers quantify speed and stability.
Run the benchmark suite to compare kham-core against nlpo3 and PyThaiNLP on a sample Thai text.
High-intent search queries and answers about installing and using this skill.
To benchmark Thai word segmentation, run automated cross-tool tests comparing kham-core, nlpo3, and PyThaiNLP on Thai text samples. The suite outputs mean, p50, and p99 timing metrics to help you identify speed regressions and bottlenecks.
Yes, comparing segmentation speed requires the Rust toolchain to run cargo bench for kham-core, and Python to execute the comparison script for nlpo3 and PyThaiNLP. Both environments are needed to generate the timing statistics.
Profiling Thai text segmentation generates mean, p50, and p99 timing metrics. These statistics help you spot performance regressions and identify bottlenecks across kham-core, nlpo3, and PyThaiNLP on diverse Thai text data.
Yes, you can use segmentation benchmarks for PR validation and performance regression testing. The automated cross-tool benchmarks quantify speed and stability, generating p50 and p99 metrics to detect regressions on Thai text samples.
The best way to evaluate segmentation bottlenecks is running automated cross-tool benchmarks on kham-core, nlpo3, and PyThaiNLP. The generated mean, p50, and p99 timing statistics pinpoint speed regressions and stability issues across diverse Thai text inputs.
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