A 12B model that rewrites AI-written drafts (emails, essays, reports, forum posts; English and Chinese) so they read like a person wrote them. It is trained to keep every number, unit, date, name and quote, and to add nothing. No AI detector was used anywhere in training.
This Space runs the bf16 weights from jialinyyzz/humanizer
on ZeroGPU, up to about 2,100 English words or 3,600 Chinese characters per run: anything over 700 words
or 1,200 characters is split at paragraph breaks and rewritten part by part, and if the GPU stops partway
the finished text stays on screen with a note. The /humanize API still takes one part (700 words) per call. Real
before/after pairs from the held-out evaluation set are on the page and need no GPU.
As in the desktop app, you can import the text of a .docx or PDF (up to 10 MB), and select any passage in the
draft and click Create fact to keep it word for word: the passage is swapped for a placeholder the model copies
through, then put back, and a part that loses it is rewritten (up to 3 tries) instead of being shown changed.
An English draft that comes back in Chinese is sampled again automatically.
Run it on your own computer: the desktop app for macOS (Apple silicon) and Windows is on
GitHub Releases; the command-line tool
hz and llama.cpp, MLX, transformers and vLLM steps are in
USAGE.md
(中文) and
AGENTS.md.
Measured, not promised: 95% judged human. On our 210 English evaluation drafts, Originality.ai (AI Allowance 0%, its strictest setting; bf16 weights, 2026-10-02) flagged 11 as AI (the previous release: 26). On the Q8_0 file you download, a strict LLM judge found no factual problem in 376 of 420 English rewrites, and more than 9 in 10 of the fixes it did list are a single word or phrase. Chinese is still catching up (no factual problem in 149 of 204). Still, read the result before you send it, especially numbers, dates, names (and the direction of every claim).
API: gradio_client → Client("jialinyyzz/humanizer").predict(draft, api_name="/humanize") returns
the rewrite plus copy rate and any numbers missing from it.
Privacy: the Space keeps no text. It logs counts only (lengths, timing, copy rate), never the draft, the output or your IP. An imported file is deleted as soon as its text has been read.
Source of this Space: space/ in the GitHub repo.
把 AI 写的草稿改成读起来像人写的，训练目标是数字、单位、日期、人名、引语原样保留。中英文都行。训练全程没有用任何 AI 检测器。 这里可以在线试一篇，也可以导入 .docx 或 PDF（最大 10 MB，读完即删）；在草稿里选中一段文字点「原样保留」，改写时这段一字不改。想装到自己电脑上，下载 App（macOS / Windows）， 或者看 不用 App 怎么用。
A 12B model that rewrites AI-written drafts (emails, essays, reports, forum posts; English and Chinese) so they read like a person wrote them. It is trained to keep every number, unit, date, name and quote, and to add nothing. No AI detector was used anywhere in training.
This Space runs the bf16 weights from jialinyyzz/humanizer
on ZeroGPU, up to about 2,100 English words or 3,600 Chinese characters per run: anything over 700 words
or 1,200 characters is split at paragraph breaks and rewritten part by part, and if the GPU stops partway
the finished text stays on screen with a note. The /humanize API still takes one part (700 words) per call. Real
before/after pairs from the held-out evaluation set are on the page and need no GPU.
As in the desktop app, you can import the text of a .docx or PDF (up to 10 MB), and select any passage in the
draft and click Create fact to keep it word for word: the passage is swapped for a placeholder the model copies
through, then put back, and a part that loses it is rewritten (up to 3 tries) instead of being shown changed.
An English draft that comes back in Chinese is sampled again automatically.
Run it on your own computer: the desktop app for macOS (Apple silicon) and Windows is on
GitHub Releases; the command-line tool
hz and llama.cpp, MLX, transformers and vLLM steps are in
USAGE.md
(中文) and
AGENTS.md.
Measured, not promised: 95% judged human. On our 210 English evaluation drafts, Originality.ai (AI Allowance 0%, its strictest setting; bf16 weights, 2026-10-02) flagged 11 as AI (the previous release: 26). On the Q8_0 file you download, a strict LLM judge found no factual problem in 376 of 420 English rewrites, and more than 9 in 10 of the fixes it did list are a single word or phrase. Chinese is still catching up (no factual problem in 149 of 204). Still, read the result before you send it, especially numbers, dates, names (and the direction of every claim).
API: gradio_client → Client("jialinyyzz/humanizer").predict(draft, api_name="/humanize") returns
the rewrite plus copy rate and any numbers missing from it.
Privacy: the Space keeps no text. It logs counts only (lengths, timing, copy rate), never the draft, the output or your IP. An imported file is deleted as soon as its text has been read.
Source of this Space: space/ in the GitHub repo.
把 AI 写的草稿改成读起来像人写的，训练目标是数字、单位、日期、人名、引语原样保留。中英文都行。训练全程没有用任何 AI 检测器。 这里可以在线试一篇，也可以导入 .docx 或 PDF（最大 10 MB，读完即删）；在草稿里选中一段文字点「原样保留」，改写时这段一字不改。想装到自己电脑上，下载 App（macOS / Windows）， 或者看 不用 App 怎么用。
