Instructions to use IshaanDaGOAT/anubis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use IshaanDaGOAT/anubis with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="IshaanDaGOAT/anubis", filename="anubis-1.0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use IshaanDaGOAT/anubis 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 IshaanDaGOAT/anubis # Run inference directly in the terminal: llama cli -hf IshaanDaGOAT/anubis
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf IshaanDaGOAT/anubis # Run inference directly in the terminal: llama cli -hf IshaanDaGOAT/anubis
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 IshaanDaGOAT/anubis # Run inference directly in the terminal: ./llama-cli -hf IshaanDaGOAT/anubis
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 IshaanDaGOAT/anubis # Run inference directly in the terminal: ./build/bin/llama-cli -hf IshaanDaGOAT/anubis
Use Docker
docker model run hf.co/IshaanDaGOAT/anubis
- LM Studio
- Jan
- Ollama
How to use IshaanDaGOAT/anubis with Ollama:
ollama run hf.co/IshaanDaGOAT/anubis
- Unsloth Studio
How to use IshaanDaGOAT/anubis with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for IshaanDaGOAT/anubis to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for IshaanDaGOAT/anubis to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for IshaanDaGOAT/anubis to start chatting
- Pi
How to use IshaanDaGOAT/anubis with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf IshaanDaGOAT/anubis
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "IshaanDaGOAT/anubis" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use IshaanDaGOAT/anubis with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf IshaanDaGOAT/anubis
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 IshaanDaGOAT/anubis
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use IshaanDaGOAT/anubis with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf IshaanDaGOAT/anubis
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 "IshaanDaGOAT/anubis" \ --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"
- Docker Model Runner
How to use IshaanDaGOAT/anubis with Docker Model Runner:
docker model run hf.co/IshaanDaGOAT/anubis
- Lemonade
How to use IshaanDaGOAT/anubis with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull IshaanDaGOAT/anubis
Run and chat with the model
lemonade run user.anubis-{{QUANT_TAG}}List all available models
lemonade list
Anubis 1.0
A small, local, conversational AI assistant โ part of the Pantheon project, a set of named, specialized AI models fine-tuned on top of open-weight base models and run entirely locally through Ollama.
Anubis is the pantheon's general chatbot: no tools, no internet access, no external actions โ just conversation, questions, and explanations, answered from what the model already knows.
What this is
- Base model: unsloth/Qwen3-8B-unsloth-bnb-4bit (Qwen3-8B, 8.2B parameters), fine-tuned with QLoRA (LoRA rank 16, ~43.6M trainable parameters, 0.53% of the full model).
- Format: GGUF, quantized to
q4_k_mfor efficient local inference. - What the fine-tune actually changed: identity (he knows he's Anubis, and uses he/him pronouns), tone, and โ most importantly โ honesty about his own limits. The fine-tuning data was a small, hand-written set of example conversations teaching him to say plainly when he doesn't know something or can't do something, rather than guessing and presenting a guess as fact.
What this fine-tune did not do
Fine-tuning on a small example set does not add general capability beyond what the base model already has โ it reshapes behavior on top of existing capability, it doesn't create new capability. Anubis's ability to hold a conversation comes from Qwen3-8B's own pretraining, not from this fine-tune.
Known limitation (found via manual review, not hidden)
With only a handful of training examples, Anubis's identity isn't perfectly anchored purely in the model weights โ early testing found he would sometimes introduce himself as "Qwen, made by Alibaba" (his base model's own pretrained self-identity) instead of Anubis, and would sometimes describe capabilities he doesn't actually have (e.g. mentioning file-scanning) when asked very open-ended "what can you do" questions, even though his system prompt is explicit that he has none. Both were mitigated with explicit rules in the system prompt above (see rules 7-8) and retesting no longer reproduces the Alibaba mix-up specifically. He never actually attempts a tool call regardless (verified automatically) โ the risk here is purely in how he describes himself, not in any real action.
How to run
Directly from Hugging Face, no download step needed:
ollama run hf.co/IshaanDaGOAT/anubis
Or locally from a clone of this repo:
ollama create anubis -f Modelfile
ollama run anubis
The Modelfile/system file in this repo contain his real system prompt. No external tools,
accounts, or internet access are required to run him.
License
Apache 2.0, inherited from the base model.
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