Instructions to use huginnfork/Qwen3.8-27B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use huginnfork/Qwen3.8-27B-FP8 with Transformers:

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

pipe = pipeline("image-text-to-text", model="huginnfork/Qwen3.8-27B-FP8")
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("huginnfork/Qwen3.8-27B-FP8")
model = AutoModelForMultimodalLM.from_pretrained("huginnfork/Qwen3.8-27B-FP8", 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 huginnfork/Qwen3.8-27B-FP8 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "huginnfork/Qwen3.8-27B-FP8"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "huginnfork/Qwen3.8-27B-FP8",
		"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/huginnfork/Qwen3.8-27B-FP8

SGLang

How to use huginnfork/Qwen3.8-27B-FP8 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 "huginnfork/Qwen3.8-27B-FP8" \
    --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": "huginnfork/Qwen3.8-27B-FP8",
		"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 "huginnfork/Qwen3.8-27B-FP8" \
        --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": "huginnfork/Qwen3.8-27B-FP8",
		"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 huginnfork/Qwen3.8-27B-FP8 with Docker Model Runner:
```
docker model run hf.co/huginnfork/Qwen3.8-27B-FP8
```

huginnfork commited on about 1 month ago

Commit

1b2027b

verified ·

1 Parent(s): 48581fc

Upload kld_qwen3.8-27b-official-fp8-asdeployed.json with huggingface_hub

Browse files

Files changed (1) hide show

kld_qwen3.8-27b-official-fp8-asdeployed.json +28 -0

kld_qwen3.8-27b-official-fp8-asdeployed.json ADDED Viewed

	@@ -0,0 +1,28 @@

+{
+  "mean_kld_nats": 0.10007637087255716,
+  "max_sample_kld_nats": 0.20761381089687347,
+  "max_token_kld_nats": 20.287128448486328,
+  "per_sample": [
+    0.0668509230017662,
+    0.010147789493203163,
+    0.20761381089687347,
+    0.1795961707830429,
+    0.05302218347787857,
+    0.17444948852062225,
+    0.03036641888320446,
+    0.07856418192386627
+  ],
+  "per_sample_max_token": [
+    2.5722639560699463,
+    0.5152737498283386,
+    20.287128448486328,
+    16.02634048461914,
+    3.8741085529327393,
+    16.518842697143555,
+    1.0826311111450195,
+    4.257715702056885
+  ],
+  "num_samples": 8,
+  "max_seq": 1024,
+  "dataset": "neuralmagic/calibration"
+}