How to use from
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 WKHGlobal/semios-node-models:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf WKHGlobal/semios-node-models:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf WKHGlobal/semios-node-models:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf WKHGlobal/semios-node-models: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 WKHGlobal/semios-node-models:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf WKHGlobal/semios-node-models: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 WKHGlobal/semios-node-models:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf WKHGlobal/semios-node-models:Q4_K_M
Use Docker
docker model run hf.co/WKHGlobal/semios-node-models:Q4_K_M
Quick Links

Semios node models (distribution lane)

Public byte-source for Semios node bootstrap, mirrored from the Semios master (mesh.semios.global/install/models/). Files are addressed by exact filename and verified client-side against sha256 pins in the node installer manifest (packaging/peer_model_manifest.json).

file sha256
curator-slm-v6.Q4_K_M.gguf b278a09472df557c8eb3a8a44cbdc1be65da9431a7cf5581ea506466b4a3d3a5
DeepSeek-Coder-V2-Lite-Instruct-Q4_K_M.gguf 603bd3f8a0281d16571da7c08bd661ee17ff0d1be6fcbd1b42242da257ef0bb8

curator-slm-v6 is a WKH/Semios mint (LoRA SFT+DPO of Qwen3-4B-Instruct-2507, WACS-signed). DeepSeek-Coder-V2-Lite-Instruct is an upstream mirror of bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF (Q4_K_M), re-published for install-lane resilience under its original license.

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GGUF
Model size
4B params
Architecture
qwen3
Hardware compatibility
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