Authorization notice. Humanizer Local Model is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.
Who it is forA researcher, writer or team member who has a long AI-drafted paper, article or report file and wants the prose rewritten without redoing headings, tables or links by hand.
The problemRewriting a long file piece by piece is slow, and it is easy to lose a number or a structural element along the way.
The outcomeA rewritten output file with headings, code blocks, tables and links kept as they were, plus a per-piece report of any number that went missing or was added.
What you need first
- A Mac with Apple silicon (M1 or newer) or a Windows x64 PC, for the app
- Enough free disk space and memory for the model; the app suggests a size for your machine, down to 8 GB machines
- Python 3.8 or newer for the hz command line tool
- llama.cpp (llama-server), curl and jq for the one-command server route
Steps
- Install the app from Option 1 or set up llama-server from Option 2 so a local model is available.
- Run
pipx install git+https://github.com/sgaofen/humanizer-local-model(orpip install git+https://github.com/sgaofen/humanizer-local-model). - For a .docx file, run
pipx inject humanize-model python-docx. - Run
hz paper.md -o paper.out.md(replace the file names with yours). - Read the warnings on stderr for any missing or new number, then read the whole output, since names and meaning are not checked.
Prompt for your agent
Using the sgaofen/humanizer-local-model repo, install the hz tool with pipx and run `hz <input-file> -o <output-file>` on the target document. Expected output: a rewritten file with structure preserved. Verify that the stderr report lists no lost or added numbers, or that each listed piece has been checked by hand.
Caveat. The README warns that in a .docx, bold or italic inside a paragraph is lost, and that names and the meaning of sentences are not checked.
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