Instructions to use DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 with Transformers:

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

pipe = pipeline("image-text-to-text", model="DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1")
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("DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1")
model = AutoModelForMultimodalLM.from_pretrained("DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1",
		"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/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1

SGLang

How to use DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 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 "DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1" \
    --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": "DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1",
		"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 "DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1" \
        --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": "DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1",
		"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"
						}
					}
				]
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 with Docker Model Runner:
```
docker model run hf.co/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1
```

DavidAU commited on Sep 16

Commit

8faa152

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1 Parent(s): 9c44193

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@@ -80,6 +80,32 @@ and takes 7-10 days to "run"; run time is due to hardware limits.
 Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic is an example a model built using this pipeline, as well as the TWO 40B Qwen 3.6s ("Eleanor" (10 stages),
 and "Grand Intelligence" (9 stages)) versions and the newest (soon to be released) "Qwen3.6-27B-V1.1-FF711-Darker-Hero-GAIN-H2.0" (working title, 8 stages).
 <B>Timeline for "Qwen3.8-27B-Cold-Fusion-GAIN-V1.1":</b>
 - DONE: Primary cook[s]. ; 1st complete ; primary testing next. || maybe additional "cook(s)".
 - DONE: BENCHES: Primary cook, Qwen 3.8 27B non trained, and 3.5/3.6 to compare...

 Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic is an example a model built using this pipeline, as well as the TWO 40B Qwen 3.6s ("Eleanor" (10 stages),
 and "Grand Intelligence" (9 stages)) versions and the newest (soon to be released) "Qwen3.6-27B-V1.1-FF711-Darker-Hero-GAIN-H2.0" (working title, 8 stages).
+---
+<h2>The SUPER Qwen Universe - 40B, 27B and 9B ; meet the performance trendsetters:</h2>
+---
+Qwen3.6 27B: The strongest, overall qwen ever beating all other Qwens in total operational power with over 2300 likes // 4 million+ total downloads:
+- https://huggingface.co/DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF
+Qwen3.8 27B: The highest scoring Qwen in brute, raw intelligence, using Qwen 3.8's 3 new reasoning modes, plus token reduction (1/2 to 1/10) enhancements:
+- https://huggingface.co/DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF
+Qwen3.8 27B: Super smart and 1/2 to 1/20 the reasoning tokens AND 5 reasoning/5 instruct modes switchable on the fly (even in chat):
+- https://huggingface.co/DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF
+Qwen3.8 27B: 99% power of BF 16 at 4 and 8 bit. Power, Control and NO DE censoring for ultimate performance also with reasoning token reductions:
+- https://huggingface.co/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF
+Qwen3.6 40B: The 40B Monster, specializing in creative and research with 730+ likes and over 2 million downloads:
+- https://huggingface.co/DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF
+Qwen3.5 9B: At just 9B parameters it beats most untuned 27B models in both intelligence (640 ARC-C) and performance, plus features 5 reasoning and 5 instruct modes (Qwen 3.8) too:
+- https://huggingface.co/DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF
+---
 <B>Timeline for "Qwen3.8-27B-Cold-Fusion-GAIN-V1.1":</b>
 - DONE: Primary cook[s]. ; 1st complete ; primary testing next. || maybe additional "cook(s)".
 - DONE: BENCHES: Primary cook, Qwen 3.8 27B non trained, and 3.5/3.6 to compare...