Instructions to use SurgeFF/AriannaV4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SurgeFF/AriannaV4 with Transformers:

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("SurgeFF/AriannaV4")
model = AutoModelForMultimodalLM.from_pretrained("SurgeFF/AriannaV4", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use SurgeFF/AriannaV4 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 SurgeFF/AriannaV4:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SurgeFF/AriannaV4:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SurgeFF/AriannaV4:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SurgeFF/AriannaV4: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 SurgeFF/AriannaV4:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SurgeFF/AriannaV4: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 SurgeFF/AriannaV4:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SurgeFF/AriannaV4:Q4_K_M

Use Docker

docker model run hf.co/SurgeFF/AriannaV4:Q4_K_M

LM Studio
Jan
Ollama
How to use SurgeFF/AriannaV4 with Ollama:
```
ollama run hf.co/SurgeFF/AriannaV4:Q4_K_M
```
Unsloth Desktop

How to use SurgeFF/AriannaV4 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SurgeFF/AriannaV4:Q4_K_M

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": "SurgeFF/AriannaV4:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use SurgeFF/AriannaV4 with Docker Model Runner:
```
docker model run hf.co/SurgeFF/AriannaV4:Q4_K_M
```

Lemonade

How to use SurgeFF/AriannaV4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SurgeFF/AriannaV4:Q4_K_M

Run and chat with the model

lemonade run user.AriannaV4-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use SurgeFF/AriannaV4 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SurgeFF/AriannaV4: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 SurgeFF/AriannaV4:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use SurgeFF/AriannaV4 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SurgeFF/AriannaV4: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 "SurgeFF/AriannaV4: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"

AriannaV4

Production all-in-one local assistant for Surge's home AI fleet. AriannaV4 = google/gemma-4-12B + the Aria v4 weights merged — one standalone, multimodal core. The published gguf/ quant ladder is provided for llama.cpp / Ollama / LM Studio.

Architecture

The weights carry the core: text, reasoning, identity, memory, math, code, grammar, storytelling, tool-selection, safety, and vision-/audio-/video-understanding. Every other modality is a sidecar the core orchestrates — realtime voice (Whisper STT / Piper TTS), video generation, image generation, retrieval embeddings — never baked into the weights.

Files

Repo root — merged standalone weights (AutoModelForImageTextToText.from_pretrained).
gguf/ — GGUF quant ladder (F16 + Q2_K … Q8_0) for llama.cpp / Ollama / LM Studio.

License

Built by Sergio Williams / Surge.

Downloads last month: 6,405

Safetensors

Model size

12B params

Tensor type

BF16

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Any-to-Any

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Model tree for SurgeFF/AriannaV4

Base model

google/gemma-4-12B

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