JMS1717/ming-voice

选用指南

AI 根据 README 整理 · 2026/10/26 17:16:37

使用方式

通过桌面应用或命令行使用，支持网页界面和语音交互，也提供API接口。

查看 README 依据

- **Linux:** **Ming Voice** in your app menu, or `ming-voice` in a terminal. It starts the server in the background, waits for the model, and opens <http://localhost:8000>. `ming-voice --stop` stops it (it holds ~20 GB of VRAM), `ming-voice --status` and `ming-voice --logs` show what it's doing, `ming-voice --help` lists the rest. (Or run `./run.sh` in the folder, in the foreground.) Press **Start conversation**, allow the microphone, and talk. Pause when you're done. > Windows: keep the server window open while you use it: WSL shuts its VM down when nothing is attached. Close it

end-of-turn pause (the ~0.23 s), and it has no interrupting. Requests from several satellites take turns on the GPU. - The Wyoming protocol has no authentication, so the bridge only accepts connections from private-network addresses. `--allow <Home Assistant's address>` (or `MING_WYOMING_ALLOW`) restricts it to Home Assistant. Other options: `--port`, `--voice` (the default voice), `--services stt,tts,conversation`. ## OpenAI-compatible API The same server speaks the OpenAI API; interactive docs are at <http://localhost:8000/docs>. | Endpoint | | |---|---|

部署要求

需要Linux或Windows 11 with WSL2，GPU至少16GB显存，支持AMD RX 6800及以上或NVIDIA RTX 30系列及以上，需要约30GB可用磁盘空间。

查看 README 依据

| Startup | ~30 s (first start after install: 1–2 min to compile kernels) | | VRAM | ~20.5 GB in bf16, ~12.5 GB with int8 experts (automatic on cards under 23 GB) | | Speech quality | 1.0% word error rate when its speech is transcribed back (same as the reference implementation) | ## Quick start ### Requirements - **Linux** (x86_64): Arch, CachyOS, EndeavourOS, Manjaro, Ubuntu, Debian, Pop!_OS, Mint, Fedora, Nobara or openSUSE (others work too if they have git and curl), **or Windows 11** with WSL2 (the installer sets it up) - A GPU with **16 GB+ VRAM**:

installer sets it up with CUDA PyTorch and the code is vendor-neutral, but it hasn't been tested on a 16 GB NVIDIA card yet. Reports welcome! - ~30 GB free disk (20 GB model + Python environment) ### Install **Linux:** open a terminal and paste: ```bash curl -fsSL https://raw.githubusercontent.com/JMS1717/ming-voice/main/install.sh | bash ``` It installs what's missing (git, curl, openssl, PortAudio) with your package manager, finds your GPU, sets up Python and PyTorch for it (ROCm 7.2 or CUDA 12.8, nothing system-wide), downloads the model (~20 GB) into

已知限制

NVIDIA支持是实验性的，未在16GB显存的NVIDIA卡上测试；支持Windows和Linux，但其他系统需具备git和curl。

查看 README 依据

- **AMD** Radeon RX 6800 or newer: RX 7000 / 9000 series and Radeon PRO cards (tested on the RX 7900 XTX). On Linux it only needs the standard `amdgpu` driver that comes with your kernel: PyTorch brings its own ROCm 7.2, so there's no ROCm to install. On Windows: a recent Adrenalin driver with WSL support. - **NVIDIA** RTX 30 series or newer (e.g. RTX 3090, 4060 Ti 16 GB, 4080, 4090, 5080, 5090), with a current driver (on Linux: your distro's NVIDIA driver, e.g. `nvidia-open` on Arch/CachyOS). *Experimental:* the

installer sets it up with CUDA PyTorch and the code is vendor-neutral, but it hasn't been tested on a 16 GB NVIDIA card yet. Reports welcome! - ~30 GB free disk (20 GB model + Python environment) ### Install **Linux:** open a terminal and paste: ```bash curl -fsSL https://raw.githubusercontent.com/JMS1717/ming-voice/main/install.sh | bash ``` It installs what's missing (git, curl, openssl, PortAudio) with your package manager, finds your GPU, sets up Python and PyTorch for it (ROCm 7.2 or CUDA 12.8, nothing system-wide), downloads the model (~20 GB) into