Instructions to use Vortex5/Shadow-Siren-26B-A4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Vortex5/Shadow-Siren-26B-A4B with Transformers:

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

pipe = pipeline("image-text-to-text", model="Vortex5/Shadow-Siren-26B-A4B")
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("Vortex5/Shadow-Siren-26B-A4B")
model = AutoModelForMultimodalLM.from_pretrained("Vortex5/Shadow-Siren-26B-A4B", 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 Vortex5/Shadow-Siren-26B-A4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Vortex5/Shadow-Siren-26B-A4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Vortex5/Shadow-Siren-26B-A4B",
		"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/Vortex5/Shadow-Siren-26B-A4B

SGLang

How to use Vortex5/Shadow-Siren-26B-A4B 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 "Vortex5/Shadow-Siren-26B-A4B" \
    --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": "Vortex5/Shadow-Siren-26B-A4B",
		"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 "Vortex5/Shadow-Siren-26B-A4B" \
        --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": "Vortex5/Shadow-Siren-26B-A4B",
		"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 Vortex5/Shadow-Siren-26B-A4B with Docker Model Runner:
```
docker model run hf.co/Vortex5/Shadow-Siren-26B-A4B
```

Shadow-Siren-26B-A4B / README.md

Vortex5

Update README.md

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metadata

base_model:
  - google/gemma-4-26B-A4B-it
  - zerofata/G4-MeroMero-26B-A4B
  - ReadyArt/Serenity-26B-A4B
  - Gryphe/Pantheon-Reasoning-26B-A4B-1.1
  - ReadyArt/Dark-Scarlett-v1.0-26B-A4B
  - Darkhn/Gemma-4-26B-A4B-Animus-V14.1-FFT
library_name: transformers
tags:
  - mergekit
  - merge
  - roleplay
  - storytelling
license: apache-2.0

Overview

Shadow-Siren-26B-A4B was created through a multi-stage merge combining G4-MeroMero-26B-A4B, Serenity-26B-A4B, Gemma-4-26B-A4B-it, Pantheon-Reasoning-26B-A4B-1.1, Dark-Scarlett-v1.0-26B-A4B, and Gemma-4-26B-A4B-Animus-V14.1-FFT.

Multi-stage merge configuration

name: First
models:
  - model: zerofata/G4-MeroMero-26B-A4B
  - model: ReadyArt/Serenity-26B-A4B
  - model: google/gemma-4-26B-A4B-it
  - model: Gryphe/Pantheon-Reasoning-26B-A4B-1.1
merge_method: saef
parameters:
  paradox: 0.40
  strength: 0.88
  boost: 0.28
  modes: 2
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: union
---
name: Second
models:
  - model: ReadyArt/Dark-Scarlett-v1.0-26B-A4B
  - model: google/gemma-4-26B-A4B-it
  - model: Darkhn/Gemma-4-26B-A4B-Animus-V14.1-FFT
merge_method: karcher
chat_template: auto
dtype: float32
out_dtype: bfloat16
parameters:
  tol: 1e-9
  max_iter: 250
tokenizer:
  source: union
---
base_model: google/gemma-4-26B-A4B-it
models:
  - model: First
  - model: Second
merge_method: hcr
chat_template: auto
parameters:
  strength: 0.6
  retention: 0.6
  novelty: 0.36
  stability: 0.7
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: union

Intended Use

Roleplay

Character interaction, dialogue, personas, and multi-turn scenes.

Creative Writing

Drafting fiction, descriptions, dialogue, and scene variations.

Storytelling

Short stories, longer narratives, plot development, and worldbuilding.

Brainstorming

Generating concepts, outlines, alternatives, and writing ideas.