Instructions to use vectionlabs/Salience-27B-R6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use vectionlabs/Salience-27B-R6 with Transformers:

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

pipe = pipeline("image-text-to-text", model="vectionlabs/Salience-27B-R6")
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("vectionlabs/Salience-27B-R6")
model = AutoModelForMultimodalLM.from_pretrained("vectionlabs/Salience-27B-R6", 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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use vectionlabs/Salience-27B-R6 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "vectionlabs/Salience-27B-R6"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "vectionlabs/Salience-27B-R6",
		"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/vectionlabs/Salience-27B-R6

SGLang

How to use vectionlabs/Salience-27B-R6 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 "vectionlabs/Salience-27B-R6" \
    --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": "vectionlabs/Salience-27B-R6",
		"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 "vectionlabs/Salience-27B-R6" \
        --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": "vectionlabs/Salience-27B-R6",
		"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 vectionlabs/Salience-27B-R6 with Docker Model Runner:
```
docker model run hf.co/vectionlabs/Salience-27B-R6
```

Exciting!

by ponzles - opened Sep 9

Discussion

ponzles

Sep 9

I'm excited to try this fine-tune because I've had pretty good results with R4 and even R5.
Do you guys have any plans to release GGUF versions? I'm planning to use this model in Q8_0.

vectionlabs

Owner Sep 10

Thanks for the support! We're glad you enjoyed R4 and R5. Yes, we definitely plan to release GGUF versions soon, including Q8_0. Stay tuned, they should be up in a few days!

vectionlabs

Owner Sep 17

GGUFs are out! Test them out when you can.

xvcy3w

Sep 21

yo this model is really nice and also fast. It became my daily go-to qwen3.8 27b model now, thank you.

vectionlabs

Owner Sep 21

That’s amazing to hear! Thanks for the support — glad the speed and performance are hitting the sweet spot for your daily use. Let us know if you have any more feedback as you keep testing it!

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