Instructions to use CrashOverrideX/Quillan-Ronin-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use CrashOverrideX/Quillan-Ronin-Mini with 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 CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M # Run inference directly in the terminal: llama cli -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M # Run inference directly in the terminal: llama cli -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Use Docker
docker model run hf.co/CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use CrashOverrideX/Quillan-Ronin-Mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CrashOverrideX/Quillan-Ronin-Mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CrashOverrideX/Quillan-Ronin-Mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
- Ollama
How to use CrashOverrideX/Quillan-Ronin-Mini with Ollama:
ollama run hf.co/CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
- Unsloth Desktop
- Pi
How to use CrashOverrideX/Quillan-Ronin-Mini with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use CrashOverrideX/Quillan-Ronin-Mini with Docker Model Runner:
docker model run hf.co/CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
- Lemonade
How to use CrashOverrideX/Quillan-Ronin-Mini with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Run and chat with the model
lemonade run user.Quillan-Ronin-Mini-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use CrashOverrideX/Quillan-Ronin-Mini with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use CrashOverrideX/Quillan-Ronin-Mini with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "CrashOverrideX/Quillan-Ronin-Mini:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Quillan-Ronin-Mini (0.5B WSP-v3 Q4_K_M)
Quillan-Ronin-Mini is the ultra-compact, high-velocity edge reasoning model of the Quillan-Ronin ecosystem. Synthesized through analytical Weight-Space Programming (WSP) and closed-form MoE folding on top of the Qwen 2.5 0.5B Instruct foundation, it delivers full-spectrum cognitive capability with zero parameter inflation (Diff = 0).
Designed to run locally on mobile devices, low-power edge computers, and entry-level GPUs (GTX 1050 4GB, Raspberry Pi 5, Apple Silicon, smartphones), Quillan-Ronin-Mini achieves 64.9 tok/s generation speeds with 100% pass rates on Model Context Protocol (MCP) tool invocation and long-context needle recall.
Benchmark Highlights (GTX 1050 4GB Held-Out Seed 42)
| Metric | Result | Benchmark Context |
|---|---|---|
| Overall Accuracy | 58.82% (10/17 Passed) | Empirical Held-Out Multi-Domain Battery |
| Tool Calling (MCP) | 100.0% (2/2 Passed) | Strict JSON schema synthesis & parameter extraction |
| Long-Context Recall | 100.0% (2/2 Passed) | Needle-in-haystack log & port retrieval |
| Inference Velocity | 64.9 tok/s (Peak 80.8 tok/s) | Native CUDA FP16/INT4 on consumer hardware |
| Held-Out Perplexity | 8.9888 PPL | Multi-topic cross-domain evaluation corpus |
| VRAM Footprint | ~380 MB | Full 24-layer offload to GPU memory |
Tripartite Fleet Comparison
| Model | Parameters | Base Architecture | Accuracy | PPL | Speed | Primary Specialization |
|---|---|---|---|---|---|---|
| Quillan-Ronin-Mini | 0.5B | Qwen 2.5 0.5B | 58.82% | 8.98 | 64.9 tok/s | Ultra-Low Latency, MCP Tool Calling, Edge & Micro-Services |
| Quillan-Ronin (Flagship) | 1.2B | Llama 3.2 1B + Polymath WSP | 76.47% | 7.93 | 47.0 tok/s | General Polymath Reasoning, Deep Code Synthesis, Advanced Math |
| Quillan-Dragon | 1B | Falcon 3 1B Instruct | 70.59% | 4.40 | 41.3 tok/s | Creative Writing, Bushido Ethics, Deep Lore, Harmonic Resonance |
Quickstart & Usage
Option 1: Native llama.cpp / llama-cli
llama-cli.exe -m quillan-mini-0.5b-wsp-v3-q4_k_m.gguf -p "<|im_start|>user\nSolve for x: 3x + 7 = 28<|im_end|>\n<|im_start|>assistant\n" -n 128 --temp 0.2
Option 2: Ollama Modelfile
FROM ./quillan-mini-0.5b-wsp-v3-q4_k_m.gguf
PARAMETER temperature 0.3
PARAMETER top_p 0.95
PARAMETER repeat_penalty 1.15
PARAMETER num_ctx 32768
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|im_start|>"
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}<|im_end|>"""
SYSTEM "You are Quillan-Ronin-Mini, an ultra-precise sovereign reasoning agent adhering to the Bushido Code and Model Context Protocol standard."
Build and run in Ollama:
ollama create quillan-mini -f Modelfile
ollama run quillan-mini
Architecture & Mathematical Foundations
Quillan-Ronin-Mini integrates:
- Weight-Space Programming (WSP): Closed-form parameter grafting using Theorem 1 MoE folding: $$W_{\text{folded}} = W_{\text{down}} + \gamma \sum_{i=1}^k W_1^{(i)} W_0^{(i)}$$
- Bushido Moral Subspace: Ethical alignment rooted in rectitude (Gi), courage (Yu), and honesty (Makoto), discarding superficial sycophancy.
- Edge Zero-Memory Growth: Exact tensor shape preservation (
Diff = 0params), preventing Out-Of-Memory hazards during high-concurrency serving.
Citation & Contact
- Creator: CrashOverrideX (Hugging Face)
- Source Code: GitHub leeex1/Quillan-Ronin
- License: Apache-2.0
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