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

ThoxUSB-Edge

license params device

THOX-branded on-device model derived from Qwen/Qwen3.5-0.8B, fine-tuned on the THOX chat + agent/tool-use corpora and quantized for the ThoxUSB tier. Status: skeleton — weights pending fine-tune + quantize.

Intended use

On-device assistant / tool-routing for the THOX device program.

Out of scope

Not for safety-critical, medical, or legal decisions without a human in the loop.

Provenance & license

Base: Qwen/Qwen3.5-0.8B (apache-2.0).

Quantization (to be filled by measured bench)

Quant On-disk RAM/RSS tok/s CPU
Q4_K_M TBD TBD TBD

Decensor policy for this repo: public.

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