Instructions to use Naphula/Goetia-31B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Naphula/Goetia-31B-v1 with Transformers:

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

pipe = pipeline("image-text-to-text", model="Naphula/Goetia-31B-v1")
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("Naphula/Goetia-31B-v1")
model = AutoModelForMultimodalLM.from_pretrained("Naphula/Goetia-31B-v1")
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

vLLM

How to use Naphula/Goetia-31B-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Naphula/Goetia-31B-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Naphula/Goetia-31B-v1",
		"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/Naphula/Goetia-31B-v1

SGLang

How to use Naphula/Goetia-31B-v1 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 "Naphula/Goetia-31B-v1" \
    --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": "Naphula/Goetia-31B-v1",
		"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 "Naphula/Goetia-31B-v1" \
        --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": "Naphula/Goetia-31B-v1",
		"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"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Naphula/Goetia-31B-v1 with Docker Model Runner:
```
docker model run hf.co/Naphula/Goetia-31B-v1
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

⚠️ Warning: This model can produce narratives and RP that contain violent and graphic erotic content. Adjust your system prompt accordingly. Also, use Gemma 4 template for best results.

📜 Goetia 31B v1

This model was merged using the della merge method.

The merge is fully uncensored and did not have any refusals upon basic Q0 benchmark tests. It should therefore not require the use of ablations or jailbreaks.

architecture: Gemma4ForConditionalGeneration
base_model: B:/31B/google--gemma-4-31B-it
models:
  - model: B:/31B/ApocalypseParty--G4-31B-Exp-3
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/ApocalypseParty--G4-31B-SFT-v3-1-1ep
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/AuriAetherwiing--G4-31B-Musica-v1
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/BeaverAI--Artemis-31B-v1h-GGUF
    parameters:
      weight: 0.02
      density: 0.9
      epsilon: 0.09
  # - model: B:/31B/Blazed-Forge--Gemma-4-Gemsicle-31B
  #   parameters:
  #     weight: 0.1
  #     density: 0.9
  #     epsilon: 0.09
  - model: B:/31B/ConicCat--Gemma4-GarnetV2-31B
    parameters:
      weight: 0.15
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/Darkhn-Gemma-4-31B-Animus-V14.0
    parameters:
      weight: 0.15
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/DavidAU--gemma-4-31B-it-Grand-Horror-X-INTENSE-HERETIC-UNCENSORED-Thinking
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/DavidAU--gemma-4-31B-it-Mystery-Fine-Tune-HERETIC-UNCENSORED-Thinking
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/DavidAU--gemma-4-31B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/Jackrong--Gemopus-4-31B-it
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  # - model: B:/31B/kabachuha--Gemma-4-The-Deckards-Brain-31B
  #   parameters:
  #     weight: 0.1
  #     density: 0.9
  #     epsilon: 0.09
  - model: B:/31B/Lambent--Fabled-Gemma4-31B
    parameters:
      weight: 0.02
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/LatitudeGames--Equinox-31B
    parameters:
      weight: 0.02
      density: 0.9
      epsilon: 0.09
  - model: B:/31B/llmfan46--gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
    parameters:
      weight: 0.04
      density: 0.9
      epsilon: 0.09
  # - model: B:/31B/Nimbz--Gemma-4-Gembrain-31B
  #   parameters:
  #     weight: 0.1
  #     density: 0.9
  #     epsilon: 0.09
  - model: B:/31B/p-e-r-e-g-r-i-n-e--Sprinkle-Gemma-4-31B
    parameters:
      weight: 0.2
      density: 0.9
      epsilon: 0.09
  # - model: B:/31B/sophosympatheia--Mero-Artemis-31B-v0.3.1
  #   parameters:
  #     weight: 0.05
  #     density: 0.9
  #     epsilon: 0.09
  # - model: B:/31B/virtuous7373--Gemma-4-Harmonia-31B
  #   parameters:
  #     weight: 0.015
  #     density: 0.9
  #     epsilon: 0.09
  # - model: B:/31B/zerofata--G4-MeroMero-31B
  #   parameters:
  #     weight: 0.1
  #     density: 0.9
  #     epsilon: 0.09
merge_method: della
parameters:  
  lambda: 1.0
  normalize: false
  int8_mask: false
  rescale: true
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: union
chat_template: auto