skill
huggingface-tokenizers Review findings
orchestra-researchorchestra-research/ai-research-skillsupdated
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
- Stars
- 14,234
- Version
- v1
- Copies
- 0
Overview
Waxell's checks found 3 findings to review, highest severity high.
- Highest severity
- high
- Findings
- 3
- What ran
- Static analysis
A clean result means nothing alarming in what is published, not a guarantee. How the checks work
We don't republish the skill's instructions. Read them on GitHub at the reviewed commit.
Security
Security scan
Checked 2 days ago
Result
Review findings Waxell's checks found 3 findings to review, highest severity high.
Checked with static analysis: servers it launches, packages it installs at runtime, scripts piped to a shell and bundled binaries. Nothing was run. How the checks work
Findings (3)
high · 3
- high
Tells Claude to install unpinned packages (tokenizers)
SKILL.md:40 · skill_risk:S2
- high
Tells Claude to install unpinned packages (tokenizers, transformers)
SKILL.md:43 · skill_risk:S2
- high
Tells Claude to install unpinned packages (tokenizers)
references/integration.md:561 · skill_risk:S2
Versions
Version history
Each distinct content we have seen, newest first, with the verdict it got at the time.
One version so far: v1 (1.0.0), seen 2026-11-03.
See and control which skills your people use
Inside your organization, Waxell scans each skill and plugin before anyone installs it, approves what passes and publishes it to a private marketplace, and puts every MCP tool call behind one governed URL.
30 minutes. No commitment.
SOC 2 Type II attested · ISO/IEC 27001:2022 certified · HIPAA with a BAA · aligned to the EU AI Act and NIST AI RMF
More research skills and plugins
sentencepieceorchestra-researchLanguage-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight… Review findingsResearchDocuments14k
axolotlorchestra-researchExpert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support High riskResearchAI & agents14k
llama-factoryorchestra-researchExpert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support No issuesResearchEngineering14k
peft-fine-tuningorchestra-researchParameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU… Review findingsResearchDocuments14k