Instructions to use nanonets/Nanonets-OCR-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nanonets/Nanonets-OCR-s with Transformers:

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

pipe = pipeline("image-text-to-text", model="nanonets/Nanonets-OCR-s")
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("nanonets/Nanonets-OCR-s")
model = AutoModelForImageTextToText.from_pretrained("nanonets/Nanonets-OCR-s")
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 nanonets/Nanonets-OCR-s with vLLM:

Install from pip and serve model

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

SGLang

How to use nanonets/Nanonets-OCR-s 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 "nanonets/Nanonets-OCR-s" \
    --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": "nanonets/Nanonets-OCR-s",
		"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 "nanonets/Nanonets-OCR-s" \
        --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": "nanonets/Nanonets-OCR-s",
		"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 nanonets/Nanonets-OCR-s with Docker Model Runner:
```
docker model run hf.co/nanonets/Nanonets-OCR-s
```

How do I disable auto-correction of words?

#33

by cloth1975 - opened Aug 28, 2025

Discussion

cloth1975

Aug 28, 2025

Hello,

the Problem I have: I try to scan images of vocabulary tests. If they contain errors it is -intentional- for the errors to remain in the resulting text, since that is a basis for grading that test. However, nanonets-ocr-s seems to auto correct scan results.

E.g. the test literally is like (in the image the word behind the equal sign is handwritten):

Teil A: Englische Wörter auf Deutsch übersetzen (10 Punkte)
Übersetze folgende Wörter ins Deutsche.
table = Tisch
window = Spinne
pencil = Stifft
chair = Stuhl
car = Auto

Teil B: Deutsche Wörter auf Englisch übersetzen (10 Punkte)
Übersetze folgende Wörter ins Englische.
Katze = Kat
Wasser = Water
Lehrer = Teacher
Ball = Ball
Buch = Book

But the resulting text is:

Teil A: Englische Wörter auf Deutsch übersetzen (10 Punkte)
Übersetze folgende Wörter ins Deutsche.
table = Tisch
window = Fenster
pencil = Stift
chair = Stuhl
car = Auto

Teil B: Deutsche Wörter auf Englisch übersetzen (10 Punkte)
Übersetze folgende Wörter ins Englische.
Katze = Cat
Wasser = Water
Lehrer = Teacher
Ball = Ball
Buch = Book

How can I force the model to leave words alone and scan them 'as is'?

Best regards

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