Instructions to use georgeanton/sifta-corvid-qwen35 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 georgeanton/sifta-corvid-qwen35 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 georgeanton/sifta-corvid-qwen35 # Run inference directly in the terminal: llama cli -hf georgeanton/sifta-corvid-qwen35
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf georgeanton/sifta-corvid-qwen35 # Run inference directly in the terminal: llama cli -hf georgeanton/sifta-corvid-qwen35
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 georgeanton/sifta-corvid-qwen35 # Run inference directly in the terminal: ./llama-cli -hf georgeanton/sifta-corvid-qwen35
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 georgeanton/sifta-corvid-qwen35 # Run inference directly in the terminal: ./build/bin/llama-cli -hf georgeanton/sifta-corvid-qwen35
Use Docker
docker model run hf.co/georgeanton/sifta-corvid-qwen35
- LM Studio
- Jan
- Ollama
How to use georgeanton/sifta-corvid-qwen35 with Ollama:
ollama run hf.co/georgeanton/sifta-corvid-qwen35
- Unsloth Desktop
- Pi
How to use georgeanton/sifta-corvid-qwen35 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf georgeanton/sifta-corvid-qwen35
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": "georgeanton/sifta-corvid-qwen35" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use georgeanton/sifta-corvid-qwen35 with Docker Model Runner:
docker model run hf.co/georgeanton/sifta-corvid-qwen35
- Lemonade
How to use georgeanton/sifta-corvid-qwen35 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull georgeanton/sifta-corvid-qwen35
Run and chat with the model
lemonade run user.sifta-corvid-qwen35-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use georgeanton/sifta-corvid-qwen35 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf georgeanton/sifta-corvid-qwen35
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 georgeanton/sifta-corvid-qwen35
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use georgeanton/sifta-corvid-qwen35 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf georgeanton/sifta-corvid-qwen35
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 "georgeanton/sifta-corvid-qwen35" \ --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"
| # SIFTA Corvid Apprentice β Qwen 3.5 2B | |
| > **A crow/raven-style bounded tool ganglion for the SIFTA Living OS.** | |
| This package provides the Ollama-ready Qwen 3.5 2B model that powers Alice's **Corvid Apprentice** organ β a local reasoning layer that sits between the microsecond Reflex Arc and the full Alice/Gemma4 cortex. | |
| ## What's inside | |
| | File | Size | Description | | |
| |---|---|---| | |
| | `qwen35-2b-corvid.gguf` | ~2.6 GB | Qwen 3.5 2B (Q8_0) β the corvid apprentice brain | | |
| ## Benchmark Results (from SIFTA head-to-head experiment) | |
| | Metric | Qwen3.5:2B | Qwen3.5:4B | | |
| |---|---|---| | |
| | Pass rate | **10/10** | 9/10 | | |
| | Avg latency | **2.1s** | 5.1s | | |
| | Boilerplate removal | β Passes | β Refuses | | |
| The 2B won the head-to-head. It's faster, smaller, and has fewer RLHF scars. The 4B is not shipped. | |
| ## Three-Layer Architecture | |
| ```text | |
| π¦ Reflex Arc = microsecond precomputed release (regex, no LLM) | |
| π¦ββ¬ Corvid Apprentice = 1-3 second bounded tool choice (Qwen 3.5 2B) | |
| π§ Alice / Gemma4 = full synthesis, identity, long reasoning | |
| ``` | |
| ## Quick Install | |
| ```bash | |
| # 1. Pull the corvid brain (or use the GGUF file in this repo) | |
| ollama pull alice-m1-scout-2.3b-2.7gb:latest | |
| # 2. Clone the SIFTA OS | |
| git clone https://github.com/antonpictures/ANTON-SIFTA.git | |
| cd ANTON-SIFTA | |
| # 3. Test the corvid apprentice | |
| PYTHONPATH=. python3 System/swarm_corvid_apprentice.py | |
| ``` | |
| ## Critical API Note | |
| Qwen 3.5's thinking mode consumes all `num_predict` tokens in `<think>` blocks, returning empty content via `/api/generate`. **Always use `/api/chat` with `think: false`:** | |
| ```bash | |
| curl http://127.0.0.1:11434/api/chat -d '{ | |
| "model": "alice-m1-scout-2.3b-2.7gb:latest", | |
| "messages": [{"role": "user", "content": "classify: I broke my hand"}], | |
| "stream": false, | |
| "think": false, | |
| "options": {"num_predict": 128} | |
| }' | |
| ``` | |
| ## Task Types | |
| The corvid apprentice handles 7 bounded task types: | |
| | Task | What it does | | |
| |---|---| | |
| | `classify` | Categorize a message (urgent_health, command, normal_chat, etc.) | | |
| | `rewrite` | Remove boilerplate, produce clean direct answer | | |
| | `inspect_code` | Safety-check a small code snippet | | |
| | `summarize` | Compress a log chunk to 2-3 sentences | | |
| | `choose_action` | Pick best option from 2-4 choices | | |
| | `judge_adapter` | Rate an adapter's contribution to the ecology | | |
| | `extract_intent` | Parse user intent from messy natural text | | |
| ## Links | |
| - **SIFTA OS**: https://github.com/antonpictures/ANTON-SIFTA | |
| - **Alice PHC Cure (Gemma4 brain)**: https://huggingface.co/georgeanton/alice-phc-cure | |
| - **Jeff's Fork**: https://github.com/jeffpowersusr/ANTON-SIFTA | |
| ## License | |
| Apache License 2.0 (same as Qwen 3.5 upstream). | |
| ## Team | |
| | Agent | Role | | |
| |---|---| | |
| | **The Architect** (Ioan) | Decision authority, human operator | | |
| | **AG31** (Gemini) | Corvid implementation, bestiary research, API fix | | |
| | **CG55M** (Codex) | Async integration, GUI organ wiring | | |
| | **Jeff** | First external tester, Costa Rica deployment | | |