Instructions to use inclusionAI/UI-Venus-Ground-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/UI-Venus-Ground-7B with Transformers:

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

pipe = pipeline("image-text-to-text", model="inclusionAI/UI-Venus-Ground-7B")
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, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("inclusionAI/UI-Venus-Ground-7B")
model = AutoModelForImageTextToText.from_pretrained("inclusionAI/UI-Venus-Ground-7B")
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

vLLM

How to use inclusionAI/UI-Venus-Ground-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/UI-Venus-Ground-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inclusionAI/UI-Venus-Ground-7B",
		"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/inclusionAI/UI-Venus-Ground-7B

SGLang

How to use inclusionAI/UI-Venus-Ground-7B 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 "inclusionAI/UI-Venus-Ground-7B" \
    --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": "inclusionAI/UI-Venus-Ground-7B",
		"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 "inclusionAI/UI-Venus-Ground-7B" \
        --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": "inclusionAI/UI-Venus-Ground-7B",
		"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 inclusionAI/UI-Venus-Ground-7B with Docker Model Runner:
```
docker model run hf.co/inclusionAI/UI-Venus-Ground-7B
```

Improve model card: Add pipeline tag, library name, and project page

by nielsr HF Staff - opened Aug 18, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+63

-10

nielsr

Aug 18, 2025

This PR enhances the model card for UI-Venus by:

Adding pipeline_tag: image-text-to-text to the metadata, making the model discoverable under the relevant task.
Adding library_name: transformers to the metadata, enabling the "Use in Transformers" widget.
Including the project page URL and an explicit link to the GitHub repository for better context and navigation.

Please review and merge this PR if everything looks good.

Improve model card: Add pipeline tag, library name, and project page5d222cee

zengw

inclusionAI org Aug 19, 2025

Thanks for your contribution and suggestions! Some changes need additional adjustments—for example, the evaluation table related to Navi doesn’t belong to this model—so I’ll close this PR and apply the updates directly. Really appreciate your input!

zengw changed pull request status to closed Aug 19, 2025

nielsr

Aug 19, 2025

Thank you!

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