Instructions to use desva0/Qwen3.8-27B-Uncensored-W4A16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use desva0/Qwen3.8-27B-Uncensored-W4A16 with Transformers:

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

pipe = pipeline("image-text-to-text", model="desva0/Qwen3.8-27B-Uncensored-W4A16")
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("desva0/Qwen3.8-27B-Uncensored-W4A16")
model = AutoModelForMultimodalLM.from_pretrained("desva0/Qwen3.8-27B-Uncensored-W4A16", 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 desva0/Qwen3.8-27B-Uncensored-W4A16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "desva0/Qwen3.8-27B-Uncensored-W4A16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "desva0/Qwen3.8-27B-Uncensored-W4A16",
		"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/desva0/Qwen3.8-27B-Uncensored-W4A16

SGLang

How to use desva0/Qwen3.8-27B-Uncensored-W4A16 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 "desva0/Qwen3.8-27B-Uncensored-W4A16" \
    --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": "desva0/Qwen3.8-27B-Uncensored-W4A16",
		"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 "desva0/Qwen3.8-27B-Uncensored-W4A16" \
        --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": "desva0/Qwen3.8-27B-Uncensored-W4A16",
		"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 desva0/Qwen3.8-27B-Uncensored-W4A16 with Docker Model Runner:
```
docker model run hf.co/desva0/Qwen3.8-27B-Uncensored-W4A16
```

Qwen3.8-27B-Uncensored-W4A16 / quantization_config.json

desva0

W4A16 (compressed-tensors) uncensored Qwen3.8-27B for 24GB GPUs

3730026 verified 2 days ago

Raw

History Blame Contribute Delete

11.1 kB

	{
	"config_groups": {
	"group_0": {
	"targets": [
	"Linear"
	],
	"weights": {
	"num_bits": 4,
	"type": "int",
	"symmetric": true,
	"group_size": 128,
	"strategy": "group",
	"block_structure": null,
	"dynamic": false,
	"actorder": null,
	"scale_dtype": null,
	"zp_dtype": null,
	"observer": "memoryless_minmax",
	"observer_kwargs": {}
	},
	"input_activations": null,
	"output_activations": null,
	"format": "pack-quantized"
	}
	},
	"quant_method": "compressed-tensors",
	"kv_cache_scheme": null,
	"format": "pack-quantized",
	"quantization_status": "compressed",
	"global_compression_ratio": null,
	"ignore": [
	"model.visual.blocks.0.attn.qkv",
	"model.visual.blocks.0.attn.proj",
	"model.visual.blocks.0.mlp.linear_fc1",
	"model.visual.blocks.0.mlp.linear_fc2",
	"model.visual.blocks.1.attn.qkv",
	"model.visual.blocks.1.attn.proj",
	"model.visual.blocks.1.mlp.linear_fc1",
	"model.visual.blocks.1.mlp.linear_fc2",
	"model.visual.blocks.2.attn.qkv",
	"model.visual.blocks.2.attn.proj",
	"model.visual.blocks.2.mlp.linear_fc1",
	"model.visual.blocks.2.mlp.linear_fc2",
	"model.visual.blocks.3.attn.qkv",
	"model.visual.blocks.3.attn.proj",
	"model.visual.blocks.3.mlp.linear_fc1",
	"model.visual.blocks.3.mlp.linear_fc2",
	"model.visual.blocks.4.attn.qkv",
	"model.visual.blocks.4.attn.proj",
	"model.visual.blocks.4.mlp.linear_fc1",
	"model.visual.blocks.4.mlp.linear_fc2",
	"model.visual.blocks.5.attn.qkv",
	"model.visual.blocks.5.attn.proj",
	"model.visual.blocks.5.mlp.linear_fc1",
	"model.visual.blocks.5.mlp.linear_fc2",
	"model.visual.blocks.6.attn.qkv",
	"model.visual.blocks.6.attn.proj",
	"model.visual.blocks.6.mlp.linear_fc1",
	"model.visual.blocks.6.mlp.linear_fc2",
	"model.visual.blocks.7.attn.qkv",
	"model.visual.blocks.7.attn.proj",
	"model.visual.blocks.7.mlp.linear_fc1",
	"model.visual.blocks.7.mlp.linear_fc2",
	"model.visual.blocks.8.attn.qkv",
	"model.visual.blocks.8.attn.proj",
	"model.visual.blocks.8.mlp.linear_fc1",
	"model.visual.blocks.8.mlp.linear_fc2",
	"model.visual.blocks.9.attn.qkv",
	"model.visual.blocks.9.attn.proj",
	"model.visual.blocks.9.mlp.linear_fc1",
	"model.visual.blocks.9.mlp.linear_fc2",
	"model.visual.blocks.10.attn.qkv",
	"model.visual.blocks.10.attn.proj",
	"model.visual.blocks.10.mlp.linear_fc1",
	"model.visual.blocks.10.mlp.linear_fc2",
	"model.visual.blocks.11.attn.qkv",
	"model.visual.blocks.11.attn.proj",
	"model.visual.blocks.11.mlp.linear_fc1",
	"model.visual.blocks.11.mlp.linear_fc2",
	"model.visual.blocks.12.attn.qkv",
	"model.visual.blocks.12.attn.proj",
	"model.visual.blocks.12.mlp.linear_fc1",
	"model.visual.blocks.12.mlp.linear_fc2",
	"model.visual.blocks.13.attn.qkv",
	"model.visual.blocks.13.attn.proj",
	"model.visual.blocks.13.mlp.linear_fc1",
	"model.visual.blocks.13.mlp.linear_fc2",
	"model.visual.blocks.14.attn.qkv",
	"model.visual.blocks.14.attn.proj",
	"model.visual.blocks.14.mlp.linear_fc1",
	"model.visual.blocks.14.mlp.linear_fc2",
	"model.visual.blocks.15.attn.qkv",
	"model.visual.blocks.15.attn.proj",
	"model.visual.blocks.15.mlp.linear_fc1",
	"model.visual.blocks.15.mlp.linear_fc2",
	"model.visual.blocks.16.attn.qkv",
	"model.visual.blocks.16.attn.proj",
	"model.visual.blocks.16.mlp.linear_fc1",
	"model.visual.blocks.16.mlp.linear_fc2",
	"model.visual.blocks.17.attn.qkv",
	"model.visual.blocks.17.attn.proj",
	"model.visual.blocks.17.mlp.linear_fc1",
	"model.visual.blocks.17.mlp.linear_fc2",
	"model.visual.blocks.18.attn.qkv",
	"model.visual.blocks.18.attn.proj",
	"model.visual.blocks.18.mlp.linear_fc1",
	"model.visual.blocks.18.mlp.linear_fc2",
	"model.visual.blocks.19.attn.qkv",
	"model.visual.blocks.19.attn.proj",
	"model.visual.blocks.19.mlp.linear_fc1",
	"model.visual.blocks.19.mlp.linear_fc2",
	"model.visual.blocks.20.attn.qkv",
	"model.visual.blocks.20.attn.proj",
	"model.visual.blocks.20.mlp.linear_fc1",
	"model.visual.blocks.20.mlp.linear_fc2",
	"model.visual.blocks.21.attn.qkv",
	"model.visual.blocks.21.attn.proj",
	"model.visual.blocks.21.mlp.linear_fc1",
	"model.visual.blocks.21.mlp.linear_fc2",
	"model.visual.blocks.22.attn.qkv",
	"model.visual.blocks.22.attn.proj",
	"model.visual.blocks.22.mlp.linear_fc1",
	"model.visual.blocks.22.mlp.linear_fc2",
	"model.visual.blocks.23.attn.qkv",
	"model.visual.blocks.23.attn.proj",
	"model.visual.blocks.23.mlp.linear_fc1",
	"model.visual.blocks.23.mlp.linear_fc2",
	"model.visual.blocks.24.attn.qkv",
	"model.visual.blocks.24.attn.proj",
	"model.visual.blocks.24.mlp.linear_fc1",
	"model.visual.blocks.24.mlp.linear_fc2",
	"model.visual.blocks.25.attn.qkv",
	"model.visual.blocks.25.attn.proj",
	"model.visual.blocks.25.mlp.linear_fc1",
	"model.visual.blocks.25.mlp.linear_fc2",
	"model.visual.blocks.26.attn.qkv",
	"model.visual.blocks.26.attn.proj",
	"model.visual.blocks.26.mlp.linear_fc1",
	"model.visual.blocks.26.mlp.linear_fc2",
	"model.visual.merger.linear_fc1",
	"model.visual.merger.linear_fc2",
	"model.language_model.layers.0.linear_attn.in_proj_b",
	"model.language_model.layers.0.linear_attn.in_proj_a",
	"model.language_model.layers.1.linear_attn.in_proj_b",
	"model.language_model.layers.1.linear_attn.in_proj_a",
	"model.language_model.layers.2.linear_attn.in_proj_b",
	"model.language_model.layers.2.linear_attn.in_proj_a",
	"model.language_model.layers.4.linear_attn.in_proj_b",
	"model.language_model.layers.4.linear_attn.in_proj_a",
	"model.language_model.layers.5.linear_attn.in_proj_b",
	"model.language_model.layers.5.linear_attn.in_proj_a",
	"model.language_model.layers.6.linear_attn.in_proj_b",
	"model.language_model.layers.6.linear_attn.in_proj_a",
	"model.language_model.layers.8.linear_attn.in_proj_b",
	"model.language_model.layers.8.linear_attn.in_proj_a",
	"model.language_model.layers.9.linear_attn.in_proj_b",
	"model.language_model.layers.9.linear_attn.in_proj_a",
	"model.language_model.layers.10.linear_attn.in_proj_b",
	"model.language_model.layers.10.linear_attn.in_proj_a",
	"model.language_model.layers.12.linear_attn.in_proj_b",
	"model.language_model.layers.12.linear_attn.in_proj_a",
	"model.language_model.layers.13.linear_attn.in_proj_b",
	"model.language_model.layers.13.linear_attn.in_proj_a",
	"model.language_model.layers.14.linear_attn.in_proj_b",
	"model.language_model.layers.14.linear_attn.in_proj_a",
	"model.language_model.layers.16.linear_attn.in_proj_b",
	"model.language_model.layers.16.linear_attn.in_proj_a",
	"model.language_model.layers.17.linear_attn.in_proj_b",
	"model.language_model.layers.17.linear_attn.in_proj_a",
	"model.language_model.layers.18.linear_attn.in_proj_b",
	"model.language_model.layers.18.linear_attn.in_proj_a",
	"model.language_model.layers.20.linear_attn.in_proj_b",
	"model.language_model.layers.20.linear_attn.in_proj_a",
	"model.language_model.layers.21.linear_attn.in_proj_b",
	"model.language_model.layers.21.linear_attn.in_proj_a",
	"model.language_model.layers.22.linear_attn.in_proj_b",
	"model.language_model.layers.22.linear_attn.in_proj_a",
	"model.language_model.layers.24.linear_attn.in_proj_b",
	"model.language_model.layers.24.linear_attn.in_proj_a",
	"model.language_model.layers.25.linear_attn.in_proj_b",
	"model.language_model.layers.25.linear_attn.in_proj_a",
	"model.language_model.layers.26.linear_attn.in_proj_b",
	"model.language_model.layers.26.linear_attn.in_proj_a",
	"model.language_model.layers.28.linear_attn.in_proj_b",
	"model.language_model.layers.28.linear_attn.in_proj_a",
	"model.language_model.layers.29.linear_attn.in_proj_b",
	"model.language_model.layers.29.linear_attn.in_proj_a",
	"model.language_model.layers.30.linear_attn.in_proj_b",
	"model.language_model.layers.30.linear_attn.in_proj_a",
	"model.language_model.layers.32.linear_attn.in_proj_b",
	"model.language_model.layers.32.linear_attn.in_proj_a",
	"model.language_model.layers.33.linear_attn.in_proj_b",
	"model.language_model.layers.33.linear_attn.in_proj_a",
	"model.language_model.layers.34.linear_attn.in_proj_b",
	"model.language_model.layers.34.linear_attn.in_proj_a",
	"model.language_model.layers.36.linear_attn.in_proj_b",
	"model.language_model.layers.36.linear_attn.in_proj_a",
	"model.language_model.layers.37.linear_attn.in_proj_b",
	"model.language_model.layers.37.linear_attn.in_proj_a",
	"model.language_model.layers.38.linear_attn.in_proj_b",
	"model.language_model.layers.38.linear_attn.in_proj_a",
	"model.language_model.layers.40.linear_attn.in_proj_b",
	"model.language_model.layers.40.linear_attn.in_proj_a",
	"model.language_model.layers.41.linear_attn.in_proj_b",
	"model.language_model.layers.41.linear_attn.in_proj_a",
	"model.language_model.layers.42.linear_attn.in_proj_b",
	"model.language_model.layers.42.linear_attn.in_proj_a",
	"model.language_model.layers.44.linear_attn.in_proj_b",
	"model.language_model.layers.44.linear_attn.in_proj_a",
	"model.language_model.layers.45.linear_attn.in_proj_b",
	"model.language_model.layers.45.linear_attn.in_proj_a",
	"model.language_model.layers.46.linear_attn.in_proj_b",
	"model.language_model.layers.46.linear_attn.in_proj_a",
	"model.language_model.layers.48.linear_attn.in_proj_b",
	"model.language_model.layers.48.linear_attn.in_proj_a",
	"model.language_model.layers.49.linear_attn.in_proj_b",
	"model.language_model.layers.49.linear_attn.in_proj_a",
	"model.language_model.layers.50.linear_attn.in_proj_b",
	"model.language_model.layers.50.linear_attn.in_proj_a",
	"model.language_model.layers.52.linear_attn.in_proj_b",
	"model.language_model.layers.52.linear_attn.in_proj_a",
	"model.language_model.layers.53.linear_attn.in_proj_b",
	"model.language_model.layers.53.linear_attn.in_proj_a",
	"model.language_model.layers.54.linear_attn.in_proj_b",
	"model.language_model.layers.54.linear_attn.in_proj_a",
	"model.language_model.layers.56.linear_attn.in_proj_b",
	"model.language_model.layers.56.linear_attn.in_proj_a",
	"model.language_model.layers.57.linear_attn.in_proj_b",
	"model.language_model.layers.57.linear_attn.in_proj_a",
	"model.language_model.layers.58.linear_attn.in_proj_b",
	"model.language_model.layers.58.linear_attn.in_proj_a",
	"model.language_model.layers.60.linear_attn.in_proj_b",
	"model.language_model.layers.60.linear_attn.in_proj_a",
	"model.language_model.layers.61.linear_attn.in_proj_b",
	"model.language_model.layers.61.linear_attn.in_proj_a",
	"model.language_model.layers.62.linear_attn.in_proj_b",
	"model.language_model.layers.62.linear_attn.in_proj_a",
	"lm_head"
	]
	}