Музыка с ИИ
moseca
Separate vocals and instruments in the browser with Demucs.
★ 397 звёздMIT
Смотреть руководство →acestep.cpp — проект с открытым исходным кодом из категории «Музыка с ИИ» от ServeurpersoCom (ServeurpersoCom/acestep.cpp на GitHub). У него 430 звёзд на GitHub и 98 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 28 сентября 2026.
Run the ACE-Step 1.5 music generator locally in C++.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Splits songs into vocals, drums, bass, and more.
Describe a track and get audio back.
Generate music without cloud APIs.
Studio-grade sample rates and formats.
Runs on CPU, CUDA, ROCm, Metal, or Vulkan.
Compose and edit with MIDI workflows.
Download the source and move into the project folder.
git clone https://github.com/ServeurpersoCom/acestep.cpp.git
cd acestep.cppGenerate the build files and compile with CMake.
cmake -B build -DCMAKE_BUILD_TYPE=Release && cmake --build buildLaunch the compiled binary and check its help output.
./build/app --helpIt is an open-source project at ServeurpersoCom/acestep.cpp with 98 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
Yes. It is MIT licensed, so you can use it commercially with attribution.
Typically 44.1–48kHz stereo — good enough for demos and remixes.
Separation and generation run much faster on GPU, but CPU works for short tracks.
Check the model's license — the code license and model weights may differ.
Separate vocals and instruments in the browser with Demucs.
A resource-efficient music source separation model in PyTorch.
Loss functions for training audio source separation models.
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Dial-driven local music generator — GGML-powered bangers, now with more C++.
Другие проекты из категории «Музыка с ИИ» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если acestep.cpp вам не подходит.
YuE2: frontier music generation with symbolic planning, zero-shot covers, and agentic music editing.
🎵 The Ultimate Open Source Suno Alternative - Professional UI for ACE-Step 1.5 AI Music Generation. Free, local, unlimited. Stop paying for Suno!
ACE-Step — the open foundation model for music generation: full songs with vocals and lyrics in 19 languages, up to 4 minutes in about 20 seconds, Apache-2.0
Official DiffSinger code: diffusion-based singing voice synthesis and text-to-speech (AAAI 2022)
Stable Audio Tools — training and inference code for Stability's audio generation models, including Stable Audio Open, MIT
Соседние проекты из категории «Музыка с ИИ» в каталоге, ближайшие по числу звёзд к acestep.cpp — продолжайте изучать полку по обе стороны от него.
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A curated compilation of AI-driven generative music resources and projects. Explore the blend of machine learning algorithms and musical creativity.
Separate vocals and instruments in the browser with Demucs.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.