Instructions to use Muhammadreza/alduin-4b-it-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Muhammadreza/alduin-4b-it-base with Transformers:

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

pipe = pipeline("text-generation", model="Muhammadreza/alduin-4b-it-base")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Muhammadreza/alduin-4b-it-base")
model = AutoModelForMultimodalLM.from_pretrained("Muhammadreza/alduin-4b-it-base", 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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Muhammadreza/alduin-4b-it-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Muhammadreza/alduin-4b-it-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Muhammadreza/alduin-4b-it-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Muhammadreza/alduin-4b-it-base

SGLang

How to use Muhammadreza/alduin-4b-it-base 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 "Muhammadreza/alduin-4b-it-base" \
    --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": "Muhammadreza/alduin-4b-it-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Muhammadreza/alduin-4b-it-base" \
        --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": "Muhammadreza/alduin-4b-it-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use Muhammadreza/alduin-4b-it-base with Docker Model Runner:
```
docker model run hf.co/Muhammadreza/alduin-4b-it-base
```

alduin-4b-it-base / README.md

Muhammadreza

Update README.md

057a681 verified 5 months ago

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metadata

tags:
  - unsloth
  - heretic
  - uncensored
  - decensored
  - abliterated
license: gemma
library_name: transformers
pipeline_tag: text-generation
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
  To access Gemma on Hugging Face, you’re required to review and agree to
  Google’s usage license. To do this, please ensure you’re logged in to Hugging
  Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
base_model:
  - google/gemma-3-4b-it

Alduin 4B

This model is a heretic version based on Gemma 3 4B and meant to be an uncensored limitless version of the original model.

I have personally been working on how models can be uncensored and I did this on a single H100 SXM (which I believe is a little bit of an overkill for this model) on RunPod and it took a few hours of my time working and getting things to work.

The name

It comes from The world eater dragon from skyrim.

Legal Responsibility

I personally made it as a personal fun projects. If you do something illegal with this, I will take ABSOLUTELY NO RESPONSIBILITY on that. Be careful with this model.

How to run (it can be executed on Google Colab even unquantized):

from transformers import pipeline
import torch

pipe = pipeline(
    "image-text-to-text",
    model="Muhammadreza/alduin-4b-it-base",
    device="cuda",
    torch_dtype=torch.bfloat16
)

messages = [
    {
        "role": "user",
        "content": "What is the answer to life, universe and everything?"
    }
]

output = pipe(text_inputs=messages, max_new_tokens=1000)
print(output[0]["generated_text"][-1]["content"])

or if you want the vision capabilities:

messages = [
    {
        "role": "system",
        "content": "You are a helpful assistant"
    },
    {
        "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?"}
        ]
    }
]

output = pipe(text=messages, max_new_tokens=1000)
print(output[0]["generated_text"][-1]["content"])

P.S : Since I have equipment for executing this model, I personally didn't provide a quantized version. If you can, please provide Ollama friendly quantizations.

Known Issues

Image input doesn't work (Fixed)