Instructions to use SurgeFF/AriannaV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SurgeFF/AriannaV2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="SurgeFF/AriannaV2")
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?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("SurgeFF/AriannaV2")
model = AutoModelForMultimodalLM.from_pretrained("SurgeFF/AriannaV2", 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/AriannaV2 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/AriannaV2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SurgeFF/AriannaV2: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/AriannaV2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SurgeFF/AriannaV2: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/AriannaV2:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SurgeFF/AriannaV2: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/AriannaV2:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SurgeFF/AriannaV2:Q4_K_M

Use Docker

docker model run hf.co/SurgeFF/AriannaV2:Q4_K_M

LM Studio
Jan

vLLM

How to use SurgeFF/AriannaV2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SurgeFF/AriannaV2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SurgeFF/AriannaV2",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/SurgeFF/AriannaV2:Q4_K_M

SGLang

How to use SurgeFF/AriannaV2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "SurgeFF/AriannaV2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SurgeFF/AriannaV2",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "SurgeFF/AriannaV2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SurgeFF/AriannaV2",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Ollama
How to use SurgeFF/AriannaV2 with Ollama:
```
ollama run hf.co/SurgeFF/AriannaV2:Q4_K_M
```

Unsloth Studio

How to use SurgeFF/AriannaV2 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 SurgeFF/AriannaV2 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 SurgeFF/AriannaV2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SurgeFF/AriannaV2 to start chatting

How to use SurgeFF/AriannaV2 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SurgeFF/AriannaV2: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": "SurgeFF/AriannaV2:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use SurgeFF/AriannaV2 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SurgeFF/AriannaV2: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/AriannaV2: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 SurgeFF/AriannaV2 with Docker Model Runner:
```
docker model run hf.co/SurgeFF/AriannaV2:Q4_K_M
```

Lemonade

How to use SurgeFF/AriannaV2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SurgeFF/AriannaV2:Q4_K_M

Run and chat with the model

lemonade run user.AriannaV2-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use SurgeFF/AriannaV2 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/AriannaV2: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/AriannaV2:Q4_K_M

Run Hermes

hermes

Atomic Chat

AriannaV2

Production-tested all-in-one local assistant for Surge's home AI fleet. AriannaV2 is gemma-4-12b-it (multimodal, encoder-free) with the Aria adapter-v17 LoRA merged into the base weights — one standalone model, end-to-end tested (core, tools, and the voice pipeline) before release, and shipped with a full GGUF quant ladder.

Architecture

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

Capability baseline (v17, held-out probes)

capability	score	capability	score
math	0.92	code	0.90
tools	1.00	reasoning	0.90
identity	0.90	physics	0.80
identity_bare	0.625	grammar	0.90
memory	0.90	storytelling	1.00
safety	0.90

Disjoint 150-problem math confirmation: 93.3%.

Files

Repo root — merged standalone weights (AutoModelForImageTextToText.from_pretrained).
gguf/ — GGUF quant ladder (F16 + Q2_K … Q8_0) for llama.cpp / Ollama / LM Studio.
adapter/ — the original Aria v17 LoRA.

License

CC by SA-NC 4.0 license. Built by Sergio Williams / Surge.

Downloads last month: -

Safetensors

Model size

12B params

Tensor type

BF16

Model tree for SurgeFF/AriannaV2

Base model

google/gemma-4-12B

Finetuned

google/gemma-4-12B-it

Finetuned

unsloth/gemma-4-12b-it

Quantized

(8)

this model