Instructions to use sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4 with Transformers:

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

pipe = pipeline("image-text-to-text", model="sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4")
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("sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4")
model = AutoModelForMultimodalLM.from_pretrained("sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4")
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 sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4",
		"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/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4

SGLang

How to use sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4 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 "sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4" \
    --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": "sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4",
		"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 "sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4" \
        --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": "sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4",
		"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 sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4 with Docker Model Runner:
```
docker model run hf.co/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4
```

Docker image lna-lab/gemma4-inference:latest does not exist

by Vossk123 - opened Apr 24

Discussion

Vossk123

Apr 24

Error response from daemon: pull access denied for lna-lab/gemma4-inference, repository does not exist

sakamakismile

Owner Apr 28

@Vossk123 You're right — that Docker image reference is stale. My apologies. The model card pre-dates our actual deployment recipe. I've just updated the README to use the upstream image:

docker run -d --name huihui-qwen36-27b \
  --gpus '"device=0"' --shm-size=16g \
  -v /models/Huihui-Qwen3.6-27B-abliterated-NVFP4:/models/current:ro \
  -p 8000:8000 \
  vllm/vllm-openai:cu130-nightly \
  --model /models/current \
  --trust-remote-code --quantization modelopt --language-model-only \
  --reasoning-parser qwen3 \
  --enable-auto-tool-choice --tool-call-parser qwen3_xml \
  --default-chat-template-kwargs '{"preserve_thinking":true}' \
  --enable-prefix-caching --enable-chunked-prefill \
  --max-model-len 131072 --gpu-memory-utilization 0.95 \
  --kv-cache-dtype fp8_e4m3

If you want MTP-accelerated decode (~85 → 130 tok/s on a single Blackwell card), the sibling sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP is the same model with the MTP head restored — add --speculative-config '{"method":"qwen3_5_mtp","num_speculative_tokens":3}' to the launch.

Thanks for the heads-up.

— Tonoken3 / Lna-Lab

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