Instructions to use ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph with Transformers:

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

pipe = pipeline("image-text-to-text", model="ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph")
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("ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph")
model = AutoModelForMultimodalLM.from_pretrained("ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph", 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 ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph",
		"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/ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph

SGLang

How to use ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph 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 "ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph" \
    --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": "ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph",
		"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 "ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph" \
        --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": "ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph",
		"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 ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph with Docker Model Runner:
```
docker model run hf.co/ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph
```

ChartGalaxyPlusPlus-Image2SceneGraph

File size: 1,527 Bytes

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{
  "status": "passed",
  "date_utc": "2026-09-24T12:34:21.923430+00:00",
  "scope": "One standalone image-to-scene-graph inference; no benchmark accuracy evaluation.",
  "runtime": {
    "python": "3.11.14",
    "vllm": "0.20.2",
    "torch": "2.11.0",
    "transformers": "5.12.1",
    "xgrammar": "0.1.32",
    "cuda": "13.0"
  },
  "dependency_consistency_check": "passed",
  "platform": "Linux x86_64",
  "gpu": "NVIDIA RTX PRO 6000 Blackwell Server Edition, 590.48.01",
  "gpu_count": 1,
  "input_sample_id": "d3-js_horizontal_group_bar_chart_horizontal_group_bar_chart_03/sample_28444",
  "input_split": "train",
  "input_image_sha256": "78967810fd2d2da24e9eac93e7b3f0ca439d4f202404fd042f0f318bdd4671ba",
  "input_example": "Dataset repository: examples/01-layout/image.png",
  "inference_spec_sha256": "a50023c63e657eff70e2cfdd42f384eedd085ffa34898aa6d7e34cb16618bbc7",
  "requirements_sha256": "3906fb04e65a3815d7c4c4248b8ac0e8bfdacbc722ba44491be344ce225ec036",
  "finish_reason": "stop",
  "output_tokens": 11485,
  "layout_items": 128,
  "node_kinds": {
    "group": 27,
    "element": 101
  },
  "strict_json_parse": true,
  "producer_schema_checks_passed": true,
  "native_evaluator_schema_and_graph_checks_passed": true,
  "recovery_used": false,
  "raw_prediction_sha256": "bceee5f5cd9d33d5e9ead0095dfdfa572cbca752c9e35ee696dfcf4b5aad4334",
  "prediction_sha256": "2510f614f11d9df4393af8822b23386ea4a0ef5323365eb82096d8c3d8947da6",
  "model_assets_unchanged_and_hash_verified": 9,
  "accuracy_measured": false
}