Instructions to use Dharma-AI/Dharma-OCR-LITE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Dharma-AI/Dharma-OCR-LITE with Transformers:

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

pipe = pipeline("image-text-to-text", model="Dharma-AI/Dharma-OCR-LITE")
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("Dharma-AI/Dharma-OCR-LITE")
model = AutoModelForMultimodalLM.from_pretrained("Dharma-AI/Dharma-OCR-LITE", 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 Dharma-AI/Dharma-OCR-LITE with vLLM:

Install from pip and serve model

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

SGLang

How to use Dharma-AI/Dharma-OCR-LITE 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 "Dharma-AI/Dharma-OCR-LITE" \
    --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": "Dharma-AI/Dharma-OCR-LITE",
		"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 "Dharma-AI/Dharma-OCR-LITE" \
        --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": "Dharma-AI/Dharma-OCR-LITE",
		"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 Dharma-AI/Dharma-OCR-LITE with Docker Model Runner:
```
docker model run hf.co/Dharma-AI/Dharma-OCR-LITE
```

Dharma-OCR-LITE / NOTICE.txt

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	DHARMA-AI NOTICE

	Project: DharmaOCR Lite

	Copyright (c) 2026 DHARMA-AI S.A.


	1. Model artifacts
	Model weights, checkpoints, tokenizer files, configuration files, adapters, model cards,
	and related model artifacts are licensed under:

	DharmaOCR Lite Noncommercial License 2026
	SPDX-License-Identifier: LicenseRef-DharmaOCR-Lite-NC-2026

	2. Attribution
	Where attribution is required for the Model, the following form is sufficient:

	"Powered by DharmaOCR Lite by DHARMA-AI S.A., licensed under the
	DharmaOCR Lite Noncommercial License 2026."

	3. Important restrictions for the Model
	The Model is made available only for restricted noncommercial use.
	Government use is expressly excluded unless separately licensed in writing by DHARMA-AI S.A.
	Commercial use, hosted/API use, OEM/embedded use, enterprise use, and other institutional
	use require a separate written license.

	4. Privacy notice summary
	According to the release statement adopted for this repository, the released training corpus
	did not use personal information as part of the released training corpus, and any independent
	use of the software, weights, or artifacts must comply with applicable local data protection law.
	The mere licensing or distribution of the Model does not make DHARMA-AI S.A. a controller,
	processor, operator, joint controller, or equivalent with respect to downstream uses by licensees.

	5. Contact
	Commercial, enterprise, government, OEM/embedded, and hosted/API licensing:
	commercial@dharma-ai.com.br
	https://dharma-ai.com.br/