Polish tokenizer diagnostic suite
polish_suite.jsonl is a fixed, synthetic stress suite written for this
repository on 2026-08-26. It has not been copied from a corpus and makes no
claim of being held out from tokenizer training data. Each domain contains two
short examples so domain metrics are useful for inspection, not statistical
inference.
Run the benchmark with:
python3 benchmark_tokenizers.py
All dataset rows are retained. Native Hugging Face artifacts have
adapter_status=native; other formats use the local reference adapter. An
adapter_fidelity of exact means the serialized artifact contains enough
information to reproduce its behavior. core_only means the byte-BPE core is
lossless but intended pre-tokenization is missing, so its segmentation metrics
must not be ranked as if they represented the author's full tokenizer.
Metrics use Unicode code points for chars, UTF-8 bytes for bytes, and
Python Unicode \\w+ spans for words. Special tokens are disabled during
encoding and retained during decoding. Throughput is the median of repeated
whole-suite batches after one warm-up and is only comparable within the same
run, machine, and runtime. In particular, python_reference_adapter speed
measures this diagnostic adapter and is not comparable to rust_tokenizers.
This suite can catch broken round trips, unknown-token behavior, pathological segmentation, and operational cost differences. It cannot establish model quality. A defensible final ranking also needs a larger provenance-controlled held-out corpus and identical downstream language-model experiments.