How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf serenade87/qwen-coder-7b-psct2lua-gguf: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 serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf serenade87/qwen-coder-7b-psct2lua-gguf: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 serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
Use Docker
docker model run hf.co/serenade87/qwen-coder-7b-psct2lua-gguf:Q4_K_M
Quick Links

Qwen2.5-Coder-7B PSCT to Lua (GGUF)

Q4_K_M quantization of Qwen2.5-Coder-7B-Instruct fine-tuned (LoRA) on ~13,000 Yu-Gi-Oh card text + Lua script pairs from cards_en.cdb + ygopro-scripts-master.

Live demo: https://serenade87-psct-to-lua.hf.space

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