Instructions to use bartowski/kai-os_Grug-12B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bartowski/kai-os_Grug-12B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/kai-os_Grug-12B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use bartowski/kai-os_Grug-12B-GGUF 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 bartowski/kai-os_Grug-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/kai-os_Grug-12B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf bartowski/kai-os_Grug-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/kai-os_Grug-12B-GGUF: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 bartowski/kai-os_Grug-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bartowski/kai-os_Grug-12B-GGUF: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 bartowski/kai-os_Grug-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bartowski/kai-os_Grug-12B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/kai-os_Grug-12B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use bartowski/kai-os_Grug-12B-GGUF with Ollama:
```
ollama run hf.co/bartowski/kai-os_Grug-12B-GGUF:Q4_K_M
```

Unsloth Studio

How to use bartowski/kai-os_Grug-12B-GGUF 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 bartowski/kai-os_Grug-12B-GGUF 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 bartowski/kai-os_Grug-12B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for bartowski/kai-os_Grug-12B-GGUF to start chatting

How to use bartowski/kai-os_Grug-12B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bartowski/kai-os_Grug-12B-GGUF: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": "bartowski/kai-os_Grug-12B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use bartowski/kai-os_Grug-12B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bartowski/kai-os_Grug-12B-GGUF: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 bartowski/kai-os_Grug-12B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use bartowski/kai-os_Grug-12B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bartowski/kai-os_Grug-12B-GGUF: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 "bartowski/kai-os_Grug-12B-GGUF: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 bartowski/kai-os_Grug-12B-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/kai-os_Grug-12B-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/kai-os_Grug-12B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/kai-os_Grug-12B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.kai-os_Grug-12B-GGUF-Q4_K_M

List all available models

lemonade list

bartowski commited on 11 days ago

Commit

ea2c68a

verified ·

1 Parent(s): 193661b

Update metadata with huggingface_hub

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README.md +38 -0

README.md CHANGED Viewed

@@ -1,6 +1,44 @@
 ---
 quantized_by: bartowski
 pipeline_tag: any-to-any
 ---
 ## Llamacpp imatrix Quantizations of Grug-12B by kai-os

 ---
 quantized_by: bartowski
 pipeline_tag: any-to-any
+base_model: kai-os/Grug-12B
+base_model_relation: quantized
+datasets:
+- hotdogs/uka-glm-5.2
+- Scale-or-Reason/general-reasoning-ift-pairs
+- samcheng0/lumia-reasoning-sft-v1
+- HSH-Intelligence/verified-math-reasoning-3k
+- kd13/CodeDebug-Instruct-v2-Reasoning
+- Madarabr/cortex-adaptive-thinking
+- CL-From-Nothing/code_rose_initial_1_7B_SFT_10K_rollouts_Qwen3-4B-Thinking-2507_k12_t0.7_maxtok12288
+tags:
+- transformers
+- safetensors
+- fine-tuned
+- qlora
+- reasoning
+- compact-reasoning
+- gemma-4
+license: other
+model-index:
+- name: Grug-12B
+  results:
+  - task:
+      type: text-generation
+      name: EOS-only local math reasoning proxy
+    dataset:
+      name: Local 36-row math reasoning eval
+      type: local
+    metrics:
+    - type: proxy_accuracy
+      value: 1.0
+      name: Grug-12B proxy accuracy
+    - type: generated_tokens
+      value: 2482
+      name: Grug-12B total generated tokens
+    - type: avg_generated_tokens
+      value: 68.9444
+      name: Grug-12B average generated tokens
 ---
 ## Llamacpp imatrix Quantizations of Grug-12B by kai-os