Instructions to use RobinsAIWorld/kintsugi-models-frozen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use RobinsAIWorld/kintsugi-models-frozen 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 RobinsAIWorld/kintsugi-models-frozen:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RobinsAIWorld/kintsugi-models-frozen:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf RobinsAIWorld/kintsugi-models-frozen:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RobinsAIWorld/kintsugi-models-frozen: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 RobinsAIWorld/kintsugi-models-frozen:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf RobinsAIWorld/kintsugi-models-frozen: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 RobinsAIWorld/kintsugi-models-frozen:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RobinsAIWorld/kintsugi-models-frozen:Q4_K_M

Use Docker

docker model run hf.co/RobinsAIWorld/kintsugi-models-frozen:Q4_K_M

LM Studio
Jan
Ollama
How to use RobinsAIWorld/kintsugi-models-frozen with Ollama:
```
ollama run hf.co/RobinsAIWorld/kintsugi-models-frozen:Q4_K_M
```

Unsloth Studio

How to use RobinsAIWorld/kintsugi-models-frozen 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 RobinsAIWorld/kintsugi-models-frozen 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 RobinsAIWorld/kintsugi-models-frozen to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for RobinsAIWorld/kintsugi-models-frozen to start chatting

How to use RobinsAIWorld/kintsugi-models-frozen with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RobinsAIWorld/kintsugi-models-frozen: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": "RobinsAIWorld/kintsugi-models-frozen:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use RobinsAIWorld/kintsugi-models-frozen with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RobinsAIWorld/kintsugi-models-frozen: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 "RobinsAIWorld/kintsugi-models-frozen: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 RobinsAIWorld/kintsugi-models-frozen with Docker Model Runner:
```
docker model run hf.co/RobinsAIWorld/kintsugi-models-frozen:Q4_K_M
```

Lemonade

How to use RobinsAIWorld/kintsugi-models-frozen with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RobinsAIWorld/kintsugi-models-frozen:Q4_K_M

Run and chat with the model

lemonade run user.kintsugi-models-frozen-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use RobinsAIWorld/kintsugi-models-frozen with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RobinsAIWorld/kintsugi-models-frozen: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 RobinsAIWorld/kintsugi-models-frozen:Q4_K_M

Run Hermes

hermes

Atomic Chat

kintsugi-models-frozen / README.md

RobinsAIWorld

Fix license column to match upstream cardData.license (API-verified)

bb762fd verified about 18 hours ago

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	---
	license: other
	license_name: upstream-licenses
	license_link: https://huggingface.co/RobinsAIWorld/kintsugi-models-frozen#upstream-sources
	tags:
	- gguf
	- mirror
	---

	# Kintsugi frozen model mirror

	Frozen mirror of the on-device GGUF models used by Celestial Kintsugi Oracle
	(`mba.robin.kintsugitarot`). Files are byte-identical server-side copies of the upstream
	repos below (copied 2026-08-12); nothing here changes unless we change it. Model set
	sourced from [AtomicBot-ai/atomic-chat-mobile-data](https://github.com/AtomicBot-ai/atomic-chat-mobile-data) `models.json`.

	## Upstream sources

	\| File \| Upstream \| License \|
	\|---\|---\|---\|
	\| LFM2.5-1.2B-Thinking-Q4_K_M.gguf \| LiquidAI/LFM2.5-1.2B-Thinking-GGUF \| lfm1.0 (LFM Open License) \|
	\| LFM2.5-2.6B-Q4_K_M.gguf \| LiquidAI/LFM2.5-2.6B-GGUF \| lfm1.0 (LFM Open License) \|
	\| LFM2-700M-Q4_K_M.gguf \| LiquidAI/LFM2-700M-GGUF \| lfm1.0 (LFM Open License) \|
	\| LFM2-350M-Q4_K_M.gguf / Q5_K_M \| LiquidAI/LFM2-350M-GGUF \| lfm1.0 (LFM Open License) \|
	\| Q4_K_M/Qwen3.5-4B-*.gguf \| sinatras/qwen3.5-4b-split \| Apache-2.0 \|
	\| Qwen3.5-2B-Q4_K_M.gguf \| unsloth/Qwen3.5-2B-GGUF \| Apache-2.0 \|
	\| Qwen3.5-0.8B-Q4_K_M.gguf \| unsloth/Qwen3.5-0.8B-GGUF \| Apache-2.0 \|
	\| gemma-3-1b-it-Q4_K_M.gguf \| ggml-org/gemma-3-1b-it-GGUF \| gemma (Gemma license) \|
	\| SmolLM3-Q4_K_M.gguf \| ggml-org/SmolLM3-3B-GGUF \| Apache-2.0 \|
	\| Bonsai-8B-Q1_0.gguf \| prism-ml/Bonsai-8B-gguf \| Apache-2.0 \|
	\| Ternary-Bonsai-8B-Q2_0.gguf \| prism-ml/Ternary-Bonsai-8B-gguf \| Apache-2.0 \|

	Each model remains under its upstream license; consult the upstream cards before reuse.