GoHumanize Open Humanizer

io.github.GoHumanize-ai由 GitHub 帳號 GoHumanize-ai 發布v0.1.12更新於 Oct 25, 2026

Rewrite AI-styled text into natural writing with a fine-tune model.

已驗證STDIO僅桌面媒體與設計AI 與機器學習

概覽

AI 產生的概覽

本機 MCP 伺服器,讓助理用開源的 GoHumanize Humanizer 模型把 AI 風格的英文改寫成更自然的文字。

可以做什麼
  • 把一段英文改寫成更自然、更像人寫的文字,50 到 400 字效果最好,最長 1,500 字會逐段處理
  • 每次呼叫要求多份改寫,保留改動最大且長度合理的那一份
  • 查詢這個模型是什麼,以及目前使用的是哪個端點
適用情境
適合需要助理潤飾生硬、機器味重的英文草稿,或想透過 OpenAI 相容端點在本機執行小型開源改寫模型的情況。
執行需求
透過 npx 在本機執行(需要 Node.js)。需要一個 OpenAI 相容端點:自架模型(例如用 Ollama 載入已發布的 GGUF 版本),或需要 OPEN_HUMANIZER_API_KEY 的託管示範端點。選用變數:OPEN_HUMANIZER_URL、OPEN_HUMANIZER_MODEL、OPEN_HUMANIZER_SAMPLES。僅支援桌面用戶端。
安裝前請注意
預設的託管端點有速率限制、閒置時會休眠,且需要 OPEN_HUMANIZER_API_KEY;第一次請求可能耗時一到兩分鐘,在逾時 60 秒的用戶端可能失敗。送出的文字會傳到所設定的端點,使用託管端點即代表把文字交給第三方。此模型定位為教學用途,不對 AI 偵測作任何保證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 GoHumanize Open Humanizer,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

GoHumanize Open Humanizer MCP server

[npm] [Model on Hugging Face] [DOI] [License: Apache 2.0]

An MCP (Model Context Protocol) server that lets AI assistants call the GoHumanize Open Humanizer: a small open model (Qwen3-4B fine-tune, Apache-2.0) that rewrites AI-styled English text into more natural human prose.

Tools:

  • humanize_text rewrite a passage (50 to 400 words works best; longer texts are processed paragraph by paragraph, up to 1,500 words).
  • about_open_humanizer what the model is and which endpoint is in use.

The model is educational and makes no claim about AI detectors. It is separate from the production models used by GoHumanize.ai.

Several rewrites, best one returned

On modern prose the model sometimes plays safe and hands the text back almost unchanged (about one try in six). Each call asks the endpoint for five rewrites (generated in parallel, so the wait is the same) and keeps the one that moved furthest from the input while staying a sensible length. Set OPEN_HUMANIZER_SAMPLES=1 for a single request.

Links

ResourceLink
Project page and browser demogohumanize.ai/open-model
GoHumanize (the product this research comes from)gohumanize.ai
Model weights and GGUF buildsgohumanize/gohumanize-open-humanizer
Dataset, 2,883 pairs (CC-BY 4.0)gohumanize/gohumanize-open-humanizer-dataset
Dataset on Kagglegohumanize/gohumanize-open-humanizer-dataset
Code and full pipelineGoHumanize-ai/gohumanize-open-humanizer
Write-up: every step, service and resultdocs/paper.md
Archived release, citable DOI10.5281/zenodo.22843083
Python client and CLIpypi.org/project/gohumanize-open-humanizer
MCP server for AI assistantsnpm · source
Training runs, loss curves and configWeights & Biases

Use

json
{  "mcpServers": {    "gohumanize-open-humanizer": {      "command": "npx",      "args": ["-y", "gohumanize-open-humanizer-mcp"]    }  }}

Which endpoint

The model runs wherever you point the server. Running it yourself needs no key and is the recommended setup:

bash
ollama pull hf.co/gohumanize/gohumanize-open-humanizer:Q4_K_Mexport OPEN_HUMANIZER_URL=http://localhost:11434/v1export OPEN_HUMANIZER_MODEL=hf.co/gohumanize/gohumanize-open-humanizer:Q4_K_M

The hosted endpoint sleeps when idle. The first request after a quiet period waits for a GPU cold start, measured at one to two minutes; afterwards a rewrite takes a second or two. MCP clients apply their own timeout, often 60 seconds, so the first call through a client may fail even with a valid key and succeed on retry. Running the model locally avoids this entirely.

The endpoint the server falls back to is the one behind the browser demo on gohumanize.ai/open-model. It is rate-limited and requires OPEN_HUMANIZER_API_KEY, so it is not open for general use; to try the model without installing anything, use the demo on that page.

Any OpenAI-compatible server works:

json
"env": {  "OPEN_HUMANIZER_URL": "http://localhost:11434/v1",  "OPEN_HUMANIZER_MODEL": "gohumanize/open-humanizer"}

OPEN_HUMANIZER_API_KEY sets a bearer token when the endpoint needs one.

Licence

Apache-2.0.

來源:README.md,提交 5caeb64

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.12最新Sep 26, 2026

評分

已滿足適用檢查項的 50%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通25 分

    請保持端點能夠回應 MCP 握手;SourceWeft 每 30 天探測一次。

  • 已宣告認證方式10 分

    請在註冊中心條目中宣告憑證請求標頭,或保持端點能夠回應探測,以便判定其認證方式。

  • 已列出工具15 分

    請讓伺服器在無憑證時回應 tools/list,或發布可在沙箱中無憑證啟動的軟體包。

  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分