VST3 for live performance. 8 tracks, 8 AI models, 30 seconds of patience per loop. It occasionally hallucinates. Not a song generator — you still have to do the work. Stay human.
A node collection for sound design, supporting MusicGen and Stable Audio. Welcome to use and experience it.
Docker image for TTS Generation ALL IN ONE
six open source ai music models inside the DAW
Portable AI music generator with built-in timeline editor — Stable Audio, one-click install, 100% offline, Windows.
Python scripts for running stable audio open inference locally and on Modal
Local Windows app for Stable Audio Open 1.0 - 9-language UI, multilingual prompt translation, 217 presets across 15 | categories, multi-variations, batch mode, game-ready WAV output. One-file installer.
a one click windows installer and control center for gary4juce
Docker service stack for a comprehensive local ai experience, running on a normal home hardware setup with single GPU. DevOps-Dashboards included. WIP.
Docker image for stable-audio-tools: Generative models for conditional audio generation
Python CLI-tool for Stable Audio Open
Real-time AI music generation server for the OBSIDIAN Neural VST plugin. Handles audio generation via a distributed GPU provider network, Stripe Connect revenue sharing, user management, and email automation. Open source under AGPL-3.0.
Portable multi-GPU music generation server for Windows -- 8 models, one-click install, zero dependencies
AI music composition suite — generate audio with text prompts and arrange into songs with a built-in multi-track DAW. Runs locally. Built with Claude.
Hands-on examples of audio generation using Stable Audio One model with automatic CUDA/CPU device selection
GPU inference server for the OBSIDIAN Neural distributed network. Contribute your GPU, generate music in real time, share the revenue equally.
A pluggable studio tool for AI audio generation. Swap models, keep your workflow.
Marketing website and user dashboard for OBSIDIAN Neural — real-time AI music generation VST3/AU plugin. Presented at AES AIMLA 2025.
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