Instructions to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb 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/alice-Q-m1-scout-2.3b-2.7gb 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/alice-Q-m1-scout-2.3b-2.7gb # Run inference directly in the terminal: llama cli -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb # Run inference directly in the terminal: llama cli -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb
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/alice-Q-m1-scout-2.3b-2.7gb # Run inference directly in the terminal: ./llama-cli -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb
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/alice-Q-m1-scout-2.3b-2.7gb # Run inference directly in the terminal: ./build/bin/llama-cli -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb
Use Docker
docker model run hf.co/georgeanton/alice-Q-m1-scout-2.3b-2.7gb
- LM Studio
- Jan
- Ollama
How to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb with Ollama:
ollama run hf.co/georgeanton/alice-Q-m1-scout-2.3b-2.7gb
- Unsloth Desktop
- Pi
How to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb
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/alice-Q-m1-scout-2.3b-2.7gb" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb with Docker Model Runner:
docker model run hf.co/georgeanton/alice-Q-m1-scout-2.3b-2.7gb
- Lemonade
How to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull georgeanton/alice-Q-m1-scout-2.3b-2.7gb
Run and chat with the model
lemonade run user.alice-Q-m1-scout-2.3b-2.7gb-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb 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/alice-Q-m1-scout-2.3b-2.7gb
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/alice-Q-m1-scout-2.3b-2.7gb
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use georgeanton/alice-Q-m1-scout-2.3b-2.7gb with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf georgeanton/alice-Q-m1-scout-2.3b-2.7gb
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/alice-Q-m1-scout-2.3b-2.7gb" \ --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 public cortex distro update - 2026-05-10
Browse files- .gitattributes +1 -0
- Modelfile +8 -0
- README.md +30 -0
- alice-Q-m1-scout-2.3b-2.7gb.gguf +3 -0
- provenance.json +14 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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alice-Q-m1-scout-2.3b-2.7gb.gguf filter=lfs diff=lfs merge=lfs -text
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Modelfile
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FROM ./alice-Q-m1-scout-2.3b-2.7gb.gguf
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TEMPLATE {{ .Prompt }}
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RENDERER qwen3.5
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PARSER qwen3.5
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PARAMETER presence_penalty 1.5
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PARAMETER temperature 1
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PARAMETER top_k 20
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PARAMETER top_p 0.95
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README.md
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---
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license: apache-2.0
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tags:
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- sifta
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- ollama
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- qwen
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- scout
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- corvid
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library_name: ollama
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---
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# Alice Q M1 Scout 2.3B 2.7GB
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Fast Q/Corvid scout for the SIFTA Living OS.
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```bash
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ollama create alice-Q-m1-scout-2.3b-2.7gb:latest -f Modelfile
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```
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## Role
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Use this as a bounded scout/ganglion for classification, routing, short
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rewrites, summaries, and tool-intent extraction. It is not Alice's primary
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identity cortex and must not claim sensors or completed actions without
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SIFTA receipts.
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## Local State Boundary
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This model package is public species DNA. It must not include raw `.sifta_state/`
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selfhood, contacts, owner memory, camera frames, or private receipts.
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alice-Q-m1-scout-2.3b-2.7gb.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297
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size 2741180928
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provenance.json
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{
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"truth_label": "SIFTA_PUBLIC_MODEL_PROVENANCE",
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"tag": "alice-Q-m1-scout-2.3b-2.7gb:latest",
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"hf_repo": "georgeanton/alice-Q-m1-scout-2.3b-2.7gb",
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"ollama_blob": "sha256-b709d81508a078a686961de6ca07a953b895d9b286c46e17f00fb267f4f2d297",
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"architecture": "qwen3.5",
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"role": "corvid_scout",
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"verified_at": "2026-05-10",
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"verified_by": "C55M@codex",
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"notes": [
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"Fast Q/Corvid scout lane.",
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"Use /api/chat with think:false for bounded scout tasks."
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]
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}
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