Instructions to use nvidia/NVIDIA-Nemotron-Parse-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nvidia/NVIDIA-Nemotron-Parse-v1.1 with Transformers:

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

pipe = pipeline("image-text-to-text", model="nvidia/NVIDIA-Nemotron-Parse-v1.1", 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("nvidia/NVIDIA-Nemotron-Parse-v1.1", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nvidia/NVIDIA-Nemotron-Parse-v1.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nvidia/NVIDIA-Nemotron-Parse-v1.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nvidia/NVIDIA-Nemotron-Parse-v1.1",
		"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/nvidia/NVIDIA-Nemotron-Parse-v1.1

SGLang

How to use nvidia/NVIDIA-Nemotron-Parse-v1.1 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 "nvidia/NVIDIA-Nemotron-Parse-v1.1" \
    --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": "nvidia/NVIDIA-Nemotron-Parse-v1.1",
		"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 "nvidia/NVIDIA-Nemotron-Parse-v1.1" \
        --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": "nvidia/NVIDIA-Nemotron-Parse-v1.1",
		"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 nvidia/NVIDIA-Nemotron-Parse-v1.1 with Docker Model Runner:
```
docker model run hf.co/nvidia/NVIDIA-Nemotron-Parse-v1.1
```

katerynaCh commited on Nov 16, 2025

Commit

e185ab4

verified ·

1 Parent(s): af91900

Upload folder using huggingface_hub

Browse files

Files changed (2) hide show

example.py +2 -12
model.safetensors +2 -2

example.py CHANGED Viewed

@@ -3,18 +3,8 @@ from PIL import Image, ImageDraw
 from transformers import AutoModel, AutoProcessor, AutoTokenizer, AutoConfig, AutoImageProcessor, GenerationConfig
 from postprocessing import extract_classes_bboxes, transform_bbox_to_original, postprocess_text
-from hf_nemotron_parse_config import NemotronParseConfig
-from hf_nemotron_parse_modeling import NemotronParseForConditionalGeneration
-from hf_nemotron_parse_processor import NemotronParseProcessor, NemotronParseImageProcessor
-AutoConfig.register("nemotron_parse", NemotronParseConfig)
-AutoModel.register(NemotronParseConfig, NemotronParseForConditionalGeneration)
-AutoProcessor.register("nemotron_parse", NemotronParseProcessor)
-AutoImageProcessor.register("nemotron_parse", NemotronParseImageProcessor)
 # Load model and processor
-model_path = "." #nvidia/NVIDIA-Nemotron-Parse-v1.1" #Nano-12B-v2-VL-BF16"  # Or use a local path
 device = "cuda:0"
 model = AutoModel.from_pretrained(
@@ -26,7 +16,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_path)
 processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
 # Load image
-image = Image.open("../soa_1.png") #path/to/your/image.jpg")
 task_prompt = "</s><s><predict_bbox><predict_classes><output_markdown>"
 # Process image

 from transformers import AutoModel, AutoProcessor, AutoTokenizer, AutoConfig, AutoImageProcessor, GenerationConfig
 from postprocessing import extract_classes_bboxes, transform_bbox_to_original, postprocess_text
 # Load model and processor
+model_path = "nvidia/NVIDIA-Nemotron-Parse-v1.1"  # Or use a local path
 device = "cuda:0"
 model = AutoModel.from_pretrained(
 processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
 # Load image
+image = Image.open("path/to/your/image.jpg")
 task_prompt = "</s><s><predict_bbox><predict_classes><output_markdown>"
 # Process image

model.safetensors CHANGED Viewed

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