cool how Hugging Face made tokenizers 15.9× faster without changing a single token ID:
This is a dev post classified by Jev as AI dev tools (a launch), kept by the Dev Radar because it carries real work, not commentary.
cool how Hugging Face made tokenizers 15.9× faster without changing a single token ID: → SIMD splitter instead of a regex engine → cache for repeated words → merge loop that never allocates → batched model calls Same API. Rust RC out now 🚀
Posted by Victor M (30.8k followers) 18 h ago · 55 likes · 3.6k views · view the original post on X. Kept by the Dev Radar as AI dev tools. Tools mentioned: tokenizers-v1.
More dev work like this
- The Dot platform has processed 6.18B tokens this week, representing 34.33% of our… — @usedotai
- What is Jev, the tool buzzing across Silicon Valley lately? — @hayden090807
- PSA - Claude code: Turn off the prompt suggestions, save ~10% of your limits/spend — @akshdeeps_001
- 智谱 GLM Coding Plan 开启中秋加国庆双节畅享活动。 — @0xLogicrw
- 😱 什么？！仅 0.6B 本地开源决策模型在 Typed Decisions 上压过 Laya ！ — @NFT_Chen
- Runs the 2.78-trillion-parameter Kimi K3 model on a single CPU using 8 GB of RAM without… — @tom_doerr
- CLAUDE.md 里写了一堆规则，Claude Code 照样有一半当没看见，这事很多人都碰到过。 — @GitHub_Daily
- 🤯卧槽！开源圈又杀出个比 Laya 更狠的 System-1 决策核模型 AgentJev-0.6B ！ — @NFT_Chen
Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 20.7k posts from 4.9k X accounts over the last 21 days, 2.4k tools, 12 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-22 08:21 UTC. Full method.