Instructions to use Snapkitty/snapkitty-nemotron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Snapkitty/snapkitty-nemotron with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Snapkitty/snapkitty-nemotron", filename="snapkitty-nemotron.Q4_K_M.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 Snapkitty/snapkitty-nemotron 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 Snapkitty/snapkitty-nemotron:Q4_K_M # Run inference directly in the terminal: llama cli -hf Snapkitty/snapkitty-nemotron:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Snapkitty/snapkitty-nemotron:Q4_K_M # Run inference directly in the terminal: llama cli -hf Snapkitty/snapkitty-nemotron: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 Snapkitty/snapkitty-nemotron:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Snapkitty/snapkitty-nemotron: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 Snapkitty/snapkitty-nemotron:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Snapkitty/snapkitty-nemotron:Q4_K_M
Use Docker
docker model run hf.co/Snapkitty/snapkitty-nemotron:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Snapkitty/snapkitty-nemotron with Ollama:
ollama run hf.co/Snapkitty/snapkitty-nemotron:Q4_K_M
- Unsloth Studio
How to use Snapkitty/snapkitty-nemotron 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 Snapkitty/snapkitty-nemotron 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 Snapkitty/snapkitty-nemotron to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Snapkitty/snapkitty-nemotron to start chatting
- Pi
How to use Snapkitty/snapkitty-nemotron with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Snapkitty/snapkitty-nemotron:Q4_K_M
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": "Snapkitty/snapkitty-nemotron:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Snapkitty/snapkitty-nemotron with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Snapkitty/snapkitty-nemotron: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 Snapkitty/snapkitty-nemotron:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Snapkitty/snapkitty-nemotron with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Snapkitty/snapkitty-nemotron: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 "Snapkitty/snapkitty-nemotron: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"
- Docker Model Runner
How to use Snapkitty/snapkitty-nemotron with Docker Model Runner:
docker model run hf.co/Snapkitty/snapkitty-nemotron:Q4_K_M
- Lemonade
How to use Snapkitty/snapkitty-nemotron with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Snapkitty/snapkitty-nemotron:Q4_K_M
Run and chat with the model
lemonade run user.snapkitty-nemotron-Q4_K_M
List all available models
lemonade list
Add model card
Browse files
README.md
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---
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language:
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- en
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license: other
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license_name: sovereign-source-license-v2
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base_model: nvidia/Nemotron-Mini-4B-Instruct
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tags:
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- gguf
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- sovereign
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- snapkitty
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- ollama
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- coding
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- worm
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- lean4
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- prolog
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- nemotron
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model_type: nemotron
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---
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# SnapKitty Nemotron
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**Sovereign coding engine** built on Nemotron-Mini-4B · SnapKitty Collective
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Custom-trained with SnapKitty sovereign identity, constitutional constraints, and syscall token layer.
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## What makes this different from base Nemotron-Mini
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- **Zero chatbot behavior** — no greetings, no apologies, code only
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- **Syscall token layer**: `<|lean_gate|>` `<|tavily_search|>` `<|bash_exec|>` `<|receipt_seal|>`
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- **WORM sealing** — every output sealed before acceptance
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- **Prolog validation** — deterministic logic layer on every output
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- **Strictest path wins** — `rewrite_needed > rejected > approved`
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- **EmojiCode modes**: valid sovereign emoji state machine
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- **Temperature 0** — deterministic output by default
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## Run with Ollama
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```bash
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ollama pull SNAPKITTYWEST/snapkitty-nemotron
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ollama run SNAPKITTYWEST/snapkitty-nemotron
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```
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Or load the GGUF directly in any llama.cpp-compatible runtime.
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## Base model
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nvidia/Nemotron-Mini-4B-Instruct (Q4_K_M quantization, 2.7GB)
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## Trust
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THE SHARED PRIMORDIAL FOUNDATION · EIN 42-6976431 · Bel Esprit D'Accord Irrevocable Trust
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## Paper
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NAND decomposition of transformer attention: [DOI 10.5281/zenodo.21351461](https://zenodo.org/records/21351461)
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## Repo
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[github.com/SNAPKITTYWEST/foundry-f1](https://github.com/SNAPKITTYWEST/foundry-f1)
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