How to use ferrotorch/serialize-parity-v1 with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf ferrotorch/serialize-parity-v1:Q8_0 # Run inference directly in the terminal: llama cli -hf ferrotorch/serialize-parity-v1:Q8_0
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ferrotorch/serialize-parity-v1:Q8_0 # Run inference directly in the terminal: llama cli -hf ferrotorch/serialize-parity-v1:Q8_0
# 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 ferrotorch/serialize-parity-v1:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ferrotorch/serialize-parity-v1:Q8_0
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 ferrotorch/serialize-parity-v1:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ferrotorch/serialize-parity-v1:Q8_0
docker model run hf.co/ferrotorch/serialize-parity-v1:Q8_0
How to use ferrotorch/serialize-parity-v1 with Ollama:
ollama run hf.co/ferrotorch/serialize-parity-v1:Q8_0
How to use ferrotorch/serialize-parity-v1 with Docker Model Runner:
How to use ferrotorch/serialize-parity-v1 with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ferrotorch/serialize-parity-v1:Q8_0
lemonade run user.serialize-parity-v1-Q8_0
lemonade list
