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[Lane 4 · numerics] tokenizer.json parity — golden encode fixtures from Hugging Face tokenizers for the ModernBERT and mmBERT files

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Issue 类型
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活跃度
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技术栈
python
领域
machine-learning, testing

调研方向

Create scripts/tokenizer_goldens.py; use the five reference texts from #1321 and the listed edge cases, then generate goldens for both Laya tokenizer paths at the specified revision. Start by checking #1321 for its five expected rows and the Qwen fixture test header for the command and pip pin format. Done means deterministic JSON outputs with source SHA-256 and tokenizers version committed under the stated resources directory.

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描述

coding good first issue size:xs skill:numerics sub-issue

Sub-issue of #1321 (HF tokenizer.json parity for BPE encoders).

Lane: 4 · Ground truth / CI
Skill needed: Python (tokenizers, huggingface_hub). No Kotlin, no SKaiNET knowledge.
Size: xs–s (an hour or two)
Blocked by: nothing

What to do

  1. Write scripts/tokenizer_goldens.py (new file) that, given a Hub repo id, a revision and a path to a tokenizer.json, downloads the file, computes its SHA-256, and encodes a fixed list of texts with Tokenizer.from_file(...).encode(text, add_special_tokens=False). Output one JSON per tokenizer: 
    {"repo": "convaiinnovations/laya", "revision": "7b928d82…", "path": "tokenizer/tokenizer.json",
 "sha256": "…", "tokenizers_version": "0.23.3", "vocab_size_with_added": 50368,
 "cases": [{"text": "Bitte die doppelte Rechnung prüfen.", "ids": [12871, 442, …], "tokens": ["Bit", "te", …]}]}
  2. Texts: the five fixture texts from #1321 plus ~15 more that each target one feature — a lone special token (<|endoftext|>, <bos>), a non-special added token, tabs and newlines, a run of 24 spaces (ModernBERT has an added token for it), CJK, Arabic, an emoji with skin-tone modifier, decomposed vs composed accents, digits (1234567890), the empty string, a single space.
  3. Generate goldens for both Laya files: tokenizer/tokenizer.json and multilingual/tokenizer/tokenizer.json at revision 7b928d828b7b0e022f929d9bd2e44165aa270148 of https://huggingface.co/convaiinnovations/laya (Apache-2.0).
  4. Commit the two JSON files under skainet-io/skainet-io-core/src/jvmTest/resources/tokenizer-goldens/ (they are a few KB; the tokenizer files themselves are not committed — the Kotlin lane downloads them like the existing Qwen fixtures).
  5. Put the exact command line and the pip pin in the script header, in the style of the header comment of QwenByteLevelBpeTokenizerFixtureTest.kt.

Acceptance

  • Script reproduces the five reference rows quoted in #1321 byte-for-byte
  • Two golden JSON files committed, each with sha256 of the source tokenizer.json and the tokenizers version
  • Running the script twice gives identical output (deterministic ordering)
  • Result reported back on #1321

Notes

Keep the script free of SKaiNET-specific logic so the sibling repository (SKaiNET-transformers) can reuse it for its own model families. If a text makes tokenizers itself warn or behave oddly, keep the text and note it in the JSON ("note" field) — surprising oracle behaviour is exactly what the Kotlin side must match.

主要语言
Kotlin
星标
52
派生
15
平均合并
1 天 15 小时
30 天内合并 PR
36

环境准备

  • 没有 Dockerfile 或 Docker Compose 文件
  • 没有 Pull Request 模板
  • 阅读贡献指南

从这里开始

  1. 先读完整个 Issue，再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库，在一个分支上完成修改。
  4. 提交 Pull Request，并在描述里引用这个 Issue 编号。

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