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VoxCPM2 Portable 的 Pinokio 一键启动器发布

timoncool/VoxCPM2_portable-pinokio

AI 导读

timoncool 发布 VoxCPM2_portable-pinokio,这是 VoxCPM2 Portable 的 Pinokio 启动器,负责在隔离的跨平台环境中安装、启动、更新和重置应用。

正文

This repository is the Pinokio launcher for VoxCPM2 Portable — the actual app lives there. This repo only contains the scripts that Pinokio runs to install, start, update and reset the app in an isolated cross-platform environment.

Install

  1. Download and install Pinokio
  2. Open in Pinokio:
  3. Click Install inside Pinokio — it will clone the app, create a Python 3.12 venv, install PyTorch (right build for your GPU), pull the 4-5 GB VoxCPM2 model on first generation

What this launcher does

  • Isolated Python venv with Python 3.12 via uv — no system-wide installs
  • PyTorch auto-selected by GPU/OS — CUDA 12.8 (NVIDIA x64), CUDA 13.0 (aarch64), DirectML (AMD Win), ROCm 6.3 (AMD Linux), MPS/CPU (macOS), CPU fallback
  • Flash-Attention 2 cp312 wheels on NVIDIA Win/Linux (auto-skipped on unsupported GPUs, graceful SDPA fallback)
  • Triton + xformers 0.0.31.post1 pinned for torch 2.7.1 compat
  • Bundled Node.js + ffmpeg + CUDA from Pinokio's ai bundle (no separate downloads)
  • Gradio auto-picks next free port via kernel.port() — no conflicts
  • NO_AUTO_BROWSER=true env var — prevents duplicate system Chrome tab (upstream patch)
  • Cross-platform env isolation: HF_HOME, TRANSFORMERS_CACHE, TORCH_HOME, MODELSCOPE_CACHE, XDG_CACHE_HOME all point inside the launcher folder
  • Voice pack (~100 voices), VoxCPM2 model (~4-5 GB), Parakeet ASR (~670 MB, lazy) cached under app/models
  • Cross-platform: Windows / Linux x64 & aarch64 / macOS ARM & Intel

Launch modes

Menu item What it runs
Start python app.py with Gradio on auto-assigned port, full 4-tab UI (TTS / Voice Design / Cloning / LoRA)
Open Folder File explorer at Generated Audio / Models cache / Voice Pack / LoRA Checkpoints / Training Data
Update git pull launcher + app, then uv pip install -r requirements.txt --upgrade
Save Disk Space Dedup venv libraries via fs.link
Reset Wipe app/ folder (full pre-install state)

Platform support matrix

OS GPU Status Acceleration
Windows 10/11 NVIDIA RTX 40xx–50xx ✅ tested CUDA 12.8 + Triton + Flash-Attn 2 cp312
Windows 10/11 NVIDIA RTX 20xx–30xx ✅ expected CUDA 12.8 + Triton + xformers (SDPA fallback)
Linux x64 NVIDIA RTX 20xx–50xx ✅ expected CUDA 12.8 + Triton + Flash-Attn 2 cp312
Linux aarch64 NVIDIA DGX Spark / Jetson ✅ expected CUDA 13.0
Windows AMD RDNA3+ ✅ expected DirectML
Linux AMD RDNA3+ ✅ expected ROCm 6.3
macOS Apple Silicon M1–M4 ✅ expected MPS
macOS Intel ⚠️ CPU-only legacy torch 2.2.2 (no Intel-Mac wheels in newer torch)
Any CPU only ⚠️ very slow (minutes per phrase) CPU
Win/Linux NVIDIA GTX 10xx (Pascal) ⚠️ Flash-Attn unavailable CUDA 12.8 + SDPA only

Minimum: 8 GB VRAM on NVIDIA for comfortable generation. Recommended: RTX 3060+ with 12 GB VRAM.

Features (inside the app)

  • 30 languages TTS — RU / EN / ZH (+9 Chinese dialects) / AR / FR / DE / HI / IT / JA / KO / PT / ES + more
  • 48 kHz studio output via AudioVAE V2 super-resolution (16 → 48 kHz)
  • Voice Design — create voices from text descriptions (gender, age, tone, emotion, pace, accent), zero-shot
  • Voice Cloning — clone from 5-50 sec reference, ~100 voices bundled + 743 extra Russian voices on-demand
  • LoRA Auto Pipeline — drop video/podcast → ffmpeg → Parakeet TDT ASR → sentence-aware split → auto-tune → training, one click
  • LoRA Manual Mode — upload pre-cleaned clips + transcripts, official OpenBMB defaults
  • Hot-swap LoRAs across TTS / Voice Design / Cloning without restart
  • MP3 / WAV / FLAC / OGG output (MP3 default via bundled FFmpeg)
  • Live-streaming playback — audio starts playing during generation
  • i18n RU / EN interface, dark theme

Full feature list: App repo → README · Russian

Links

Support This Project

I build software and do research in AI and music/voice generation. Most of what I create is free and open source. Your donations allow me to keep creating and exploring without worrying about where the next meal comes from =)

All donation methods | dalink.to/nerual_dreming | boosty.to/neuro_art

  • BTC: 1E7dHL22RpyhJGVpcvKdbyZgksSYkYeEBC
  • ETH (ERC20): 0xb5db65adf478983186d4897ba92fe2c25c594a0c
  • USDT (TRC20): TQST9Lp2TjK6FiVkn4fwfGUee7NmkxEE7C

Author

License

MIT — same as the main VoxCPM2 Portable project. Base model VoxCPM2 is MIT-licensed by OpenBMB.


Star History

来源:GitHub · github.com