Instructions to use AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16 with Transformers:

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

pipe = pipeline("image-text-to-text", model="AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16")
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("AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16")
model = AutoModelForMultimodalLM.from_pretrained("AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16", 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 AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16",
		"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/AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16

SGLang

How to use AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16 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 "AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16" \
    --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": "AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16",
		"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 "AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16" \
        --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": "AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16",
		"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 AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16 with Docker Model Runner:
```
docker model run hf.co/AMAImedia/Qwen3.8-27B-Qwopus-Flash-NOESIS-BF16
```

NOESIS / AMAImedia

Released as part of the NOESIS Professional Multilingual Dubbing Automation Platform (framework: DHCF-FNO — Deterministic Hybrid Control Framework for Frozen Neural Operators).

Founder: Ilia Bolotnikov
Organization: AMAImedia.com
X (Twitter): @AMAImediacom
LinkedIn: Ilia Bolotnikov
Telegram: @djbionicl
Release date: 2026-09-04

Original model

Author: Jackrong
Original repository: Jackrong/Qwopus3.8-27B-Flash

Qwopus3.8-27B-Flash — NOESIS Repack

Standardized 40-shard repack of Qwopus3.8-27B-Flash for the NOESIS platform.

What this model is

This is a repacked version of Qwopus3.8-27B-Flash — a Qwen3.5-based 27B parameter model optimized for flash inference with hybrid linear attention.

The repack standardizes the model to:

40 shards (~1.3 GB each) for efficient loading
BF16 precision (bfloat16)
Qwen3.5 architecture with hybrid linear attention layers

Repack details

Property	Value
Base model	Jackrong/Qwopus3.8-27B-Flash
Architecture	Qwen3.5 (Qwen3_5ForConditionalGeneration)
Parameters	~27B
Layers	64
Shards	40
Precision	BF16
Visual encoder	model-extra-00001-of-00001.safetensors (1.7 GB)
MTP head	model-mtp.safetensors (810 MB)

Files included

model-00001-of-00040.safetensors through model-00040-of-00040.safetensors — text model weights
model-extra-00001-of-00001.safetensors — vision encoder
model-mtp.safetensors — multi-token prediction head
config.json — model configuration
tokenizer.json + tokenizer_config.json — tokenizer files
model.safetensors.index.json — shard index

Serving

python3 -m sglang.launch_server \
  --model-path AMAImedia/Qwopus3.8-27B-Flash-NOESIS-BF16 \
  --served-model-name "Qwopus3.8-27B-Flash-NOESIS" \
  --tp-size 1 \
  --context-length 262144 \
  --trust-remote-code \
  --host 0.0.0.0 --port 8000

Citation

@misc{qwopus3.8-flash-noesis-2026,
  title  = {Qwopus3.8-27B-Flash — NOESIS Repack},
  author = {AMAImedia (Ilia Bolotnikov)},
  year   = {2026},
  url    = {https://huggingface.co/AMAImedia}
}