Instructions to use sensenova/SenseNova-SI-1.1-InternVL3-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sensenova/SenseNova-SI-1.1-InternVL3-2B with Transformers:

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

pipe = pipeline("image-text-to-text", model="sensenova/SenseNova-SI-1.1-InternVL3-2B", trust_remote_code=True)
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 AutoModel
model = AutoModel.from_pretrained("sensenova/SenseNova-SI-1.1-InternVL3-2B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sensenova/SenseNova-SI-1.1-InternVL3-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sensenova/SenseNova-SI-1.1-InternVL3-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sensenova/SenseNova-SI-1.1-InternVL3-2B",
		"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/sensenova/SenseNova-SI-1.1-InternVL3-2B

SGLang

How to use sensenova/SenseNova-SI-1.1-InternVL3-2B 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 "sensenova/SenseNova-SI-1.1-InternVL3-2B" \
    --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": "sensenova/SenseNova-SI-1.1-InternVL3-2B",
		"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 "sensenova/SenseNova-SI-1.1-InternVL3-2B" \
        --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": "sensenova/SenseNova-SI-1.1-InternVL3-2B",
		"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 sensenova/SenseNova-SI-1.1-InternVL3-2B with Docker Model Runner:
```
docker model run hf.co/sensenova/SenseNova-SI-1.1-InternVL3-2B
```

Improve model card: Add pipeline tag, library name, language, and explicit links

by nielsr HF Staff - opened Nov 22, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+138

-2

nielsr

Nov 22, 2025

This PR enhances the model card by:

Adding pipeline_tag: image-text-to-text to improve discoverability on the Hugging Face Hub.
Specifying library_name: transformers to enable the automated "how to use" widget, as the model demonstrates compatibility with the 🤗 Transformers library.
Including language: en as an additional tag, reflecting the primary language of the model and its documentation.
Adding explicit "Paper" and "Code" sections with links to the arXiv paper and the GitHub repository, respectively, for clearer navigation.
The existing "QuickStart" section containing sample usage code snippets is preserved.

Improve model card: Add pipeline tag, library name, language, and explicit links9f91cb60

yl-1993 changed pull request status to merged Nov 24, 2025

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