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\n \n
\n\n
@chonkiejs/chunk
\n\n
\n the fastest text chunking library — up to 1 TB/s throughput\n
\n\n
\n \n \n \n \n \n
\n\n---\n\nyou know how every chunking library claims to be fast? yeah, we actually meant it.\n\n**@chonkiejs/chunk** splits text at semantic boundaries (periods, newlines, the usual suspects) and does it stupid fast. we're talking \"chunk the entire english wikipedia in 120ms\" fast.\n\nwant to know how? [read the blog post](https://minha.sh/posts/so,-you-want-to-chunk-really-fast) where we nerd out about SIMD instructions and lookup tables.\n\n## 📦 installation\n\n```bash\nnpm install @chonkiejs/chunk\n```\n\nlooking for [rust](https://github.com/chonkie-inc/chunk) or [python](https://github.com/chonkie-inc/chunk/tree/main/packages/python)?\n\n## 🚀 usage\n\n```javascript\nimport { init, chunk } from '@chonkiejs/chunk';\n\n// initialize wasm (required once)\nawait init();\n\nconst text = \"Hello world. How are you? I'm fine.\\nThanks for asking.\";\n\n// with defaults (4KB chunks, split at \\n . ?)\nfor (const slice of chunk(text)) {\n console.log(slice);\n}\n\n// with custom size\nfor (const slice of chunk(text, { size: 1024 })) {\n console.log(slice);\n}\n\n// with custom delimiters\nfor (const slice of chunk(text, { delimiters: \".?!\\n\" })) {\n console.log(slice);\n}\n\n// with multi-byte pattern (e.g., metaspace ▁ for SentencePiece tokenizers)\nfor (const slice of chunk(text, { pattern: \"▁\", prefix: true })) {\n console.log(slice);\n}\n\n// with consecutive pattern handling (split at START of runs, not middle)\nfor (const slice of chunk(\"word next\", { pattern: \" \", consecutive: true })) {\n console.log(slice);\n}\n\n// with forward fallback (search forward if no pattern in backward window)\nfor (const slice of chunk(text, { pattern: \" \", forwardFallback: true })) {\n console.log(slice);\n}\n\n// collect all chunks\nconst chunks = [...chunk(text)];\n```\n\npass strings and get strings back. for zero-copy performance with binary data, pass `Uint8Array` and you'll get `Uint8Array` views back.\n\n## 📝 citation\n\nif you use @chonkiejs/chunk in your research, please cite it as follows:\n\n```bibtex\n@software{chunk2025,\n author = {Minhas, Bhavnick},\n title = {chunk: The fastest text chunking library},\n year = {2025},\n publisher = {GitHub},\n howpublished = {\\url{https://github.com/chonkie-inc/chunk}},\n}\n```\n\n## 📄 license\n\nlicensed under either of [Apache License, Version 2.0](LICENSE-APACHE) or [MIT license](LICENSE-MIT) at your option.\n","readmeFilename":"README.md"}
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