Instructions to use koboldcpp/music with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use koboldcpp/music with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf koboldcpp/music:Q4_K_M # Run inference directly in the terminal: llama cli -hf koboldcpp/music:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf koboldcpp/music:Q4_K_M # Run inference directly in the terminal: llama cli -hf koboldcpp/music:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf koboldcpp/music:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf koboldcpp/music:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf koboldcpp/music:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf koboldcpp/music:Q4_K_M
Use Docker
docker model run hf.co/koboldcpp/music:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use koboldcpp/music with Ollama:
ollama run hf.co/koboldcpp/music:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use koboldcpp/music with Docker Model Runner:
docker model run hf.co/koboldcpp/music:Q4_K_M
- Lemonade
How to use koboldcpp/music with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull koboldcpp/music:Q4_K_M
Run and chat with the model
lemonade run user.music-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Thanks
Glad to see these available in a pretty easy to inject into KoboldCPP.
Though the styles (as of Ace Step 5/6 Turbo) are a bit more limited not doing heavy metal, rock, tribal or others very well. And often outputs sounding like it was recorded using a Yamaha keyboard from the 90's with a 2Mb Soundfont chip. I'm sure these will improve as newer models are put out.
Even putting the largest models with 8Gb Vram get decent output in a reasonable time (like 5-10 minutes per song), probably due to low VRAM option which swapping models as it needs rather than trying to hold the whole thing at once or relying as much on CPU.
Glad you like it!