Instructions to use Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI with Transformers:

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

pipe = pipeline("image-text-to-text", model="Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI")
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-26B-A4B-v1.3-Tainted-Heretic-ARI")
model = AutoModelForMultimodalLM.from_pretrained("Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI", 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

vLLM

How to use Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI"
# 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-26B-A4B-v1.3-Tainted-Heretic-ARI",
		"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-26B-A4B-v1.3-Tainted-Heretic-ARI

SGLang

How to use Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI 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-26B-A4B-v1.3-Tainted-Heretic-ARI" \
    --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-26B-A4B-v1.3-Tainted-Heretic-ARI",
		"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-26B-A4B-v1.3-Tainted-Heretic-ARI" \
        --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-26B-A4B-v1.3-Tainted-Heretic-ARI",
		"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-26B-A4B-v1.3-Tainted-Heretic-ARI with Docker Model Runner:
```
docker model run hf.co/Naphula/Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI
```

Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI / README.md

Naphula

Create README.md

e5a5645 verified about 2 months ago

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metadata

base_model:
  - google/gemma-4-26B-A4B
  - ApocalypseParty/G4-26B-SFT-6
  - AuriAetherwiing/G4-26B-A4B-Musica-v1
  - BeaverAI/Orion-26B-A4B-v1a-GGUF
  - BeaverAI/Orion-26B-A4B-v1b-GGUF
  - Darkhn/Gemma-4-26B-A4B-Animus-V14.1-FFT
  - Gryphe/Gemma-4-26B-A4B-StyleTune
  - Gryphe/Pantheon-Reasoning-26B-A4B-1.1
  - Locutusque/Esmeralda-Gemma4-26B-A4B
  - ReadyArt/Dark-Scarlett-v1.0-26B-A4B-GGUF
  - ReadyArt/For-Her-Darkside-26B-A4B-v1.4-GGUF
  - ReadyArt/Melody1437-26B-A4B-GGUF
  - ReadyArt/Omega-Evolution-26B-A4B-v3.0-GGUF
  - ReadyArt/Serenity-26B-A4B-GGUF
  - zerofata/G4-MeroMero-26B-A4B
language: eng
library_name: transformers
license: apache-2.0
tags:
  - merge
  - mergekit
  - moe_della
  - gemma4
  - conversational
  - roleplay
  - creative writing
  - ablated
  - uncensored
  - heretic
  - ara
  - ari
widget:
  - text: Goetia-26B-A4B-v1.3-Tainted-Heretic-ARI
    output:
      url: >-
        https://cdn-uploads.huggingface.co/production/uploads/68e840caa318194c44ec2a04/DHbuh4efzjCGpxDUciZ_-.jpeg

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

📜 Goetia 26B A4B v1.3 Tainted Heretic ARI

Metric	This model	Original model
KL divergence	0.1334	0 (by definition)
Refusals	4/100	100/100