Instructions to use webbrain-one/webbrain-vl-2-450M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use webbrain-one/webbrain-vl-2-450M with Transformers:

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

pipe = pipeline("image-text-to-text", model="webbrain-one/webbrain-vl-2-450M")
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("webbrain-one/webbrain-vl-2-450M")
model = AutoModelForMultimodalLM.from_pretrained("webbrain-one/webbrain-vl-2-450M", 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 webbrain-one/webbrain-vl-2-450M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "webbrain-one/webbrain-vl-2-450M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "webbrain-one/webbrain-vl-2-450M",
		"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/webbrain-one/webbrain-vl-2-450M

SGLang

How to use webbrain-one/webbrain-vl-2-450M 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 "webbrain-one/webbrain-vl-2-450M" \
    --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": "webbrain-one/webbrain-vl-2-450M",
		"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 "webbrain-one/webbrain-vl-2-450M" \
        --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": "webbrain-one/webbrain-vl-2-450M",
		"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 webbrain-one/webbrain-vl-2-450M with Docker Model Runner:
```
docker model run hf.co/webbrain-one/webbrain-vl-2-450M
```

webbrain-vl-2-450M / eval /v2-summary.json

webbrain-one

Publish WebBrain Browser Vision Tiny 2

7dd6050 verified 2 months ago

Raw History Blame Contribute Delete

5.66 kB

{
  "schemaVersion": 1,
  "createdAt": "2026-08-22T08:29:48.253Z",
  "model": "webbrain-browser-vision-tiny-2",
  "endpoint": "http://127.0.0.1:8000/v1/chat/completions",
  "promptMode": "production",
  "productionUserText": "Describe this screenshot of the current browser viewport for a web-automation agent. Follow the format in the system prompt.",
  "promptSha256": "8465a0e60af8f3e4dcc5ff188a7682c22b1d52974db54ccb42ff8a1a5346a207",
  "overall": {
    "cases": 100,
    "scored": 100,
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    "successRate": 0.36,
    "meanScore": 0.7499122266622266,
    "meanLatencyMs": 1967.96
  },
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    "dashboard": {
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    "photo-understanding": {
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    "security-challenge": {
      "cases": 5,
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    "uncertainty-calibration": {
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      "meanScore": 0.8200000000000001,
      "meanLatencyMs": 1990.2
    }
  }
}

	{
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	"model": "webbrain-browser-vision-tiny-2",
	"endpoint": "http://127.0.0.1:8000/v1/chat/completions",
	"promptMode": "production",
	"productionUserText": "Describe this screenshot of the current browser viewport for a web-automation agent. Follow the format in the system prompt.",
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	},
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	},
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	}
	}
	}