How to use qwrt/Melodimodell-67M with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf qwrt/Melodimodell-67M:F16 # Run inference directly in the terminal: llama cli -hf qwrt/Melodimodell-67M:F16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf qwrt/Melodimodell-67M:F16 # Run inference directly in the terminal: llama cli -hf qwrt/Melodimodell-67M:F16
# 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 qwrt/Melodimodell-67M:F16 # Run inference directly in the terminal: ./llama-cli -hf qwrt/Melodimodell-67M:F16
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 qwrt/Melodimodell-67M:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf qwrt/Melodimodell-67M:F16
docker model run hf.co/qwrt/Melodimodell-67M:F16
How to use qwrt/Melodimodell-67M with Ollama:
ollama run hf.co/qwrt/Melodimodell-67M:F16
How to use qwrt/Melodimodell-67M with Docker Model Runner:
How to use qwrt/Melodimodell-67M with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull qwrt/Melodimodell-67M:F16
lemonade run user.Melodimodell-67M-F16
lemonade list
https://huggingface.co/qwrt/Melodimodell-67M/resolve/main/losses.json
hf download hf://qwrt/Melodimodell-67M/losses.json
curl -L -o losses.json https://huggingface.co/qwrt/Melodimodell-67M/resolve/main/losses.json
