Image-Text-to-Text
Transformers
Safetensors
Portuguese
qwen2_5_vl
ocr
document-understanding
structured-extraction
specialized-small-language-model
brazilian-portuguese
conversational
text-generation-inference
compressed-tensors
Instructions to use Dharma-AI/Dharma-OCR-LITE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
| SPDX-License-Identifier: LicenseRef-DharmaOCR-Lite-NC-2026 | |
| DharmaOCR Lite Noncommercial License 2026 | |
| Based on PolyForm Noncommercial 1.0.0, as adapted by DHARMA-AI S.A. | |
| Copyright (c) 2026 DHARMA-AI S.A. | |
| This license governs the use, reproduction, distribution, modification, fine-tuning, | |
| evaluation, benchmarking, and deployment of the model weights, checkpoints, tokenizer | |
| files, configuration files, adapters, LoRA/QLoRA files, model cards, documentation, | |
| and related artifacts distributed by DHARMA-AI S.A. under this license | |
| (collectively, the "Model"). | |
| By accessing, downloading, using, reproducing, modifying, fine-tuning, evaluating, | |
| benchmarking, distributing, or otherwise exploiting the Model, you agree to be bound | |
| by this License. | |
| 1. Definitions | |
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| configuration files, artifacts, documentation, and related files distributed under | |
| this License. | |
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| You may not use the Model or any Derivative Model: | |
| (a) in violation of applicable law or regulation; | |
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| If You distribute the Model or a Derivative Model, or deploy it in any user-facing | |
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| "Powered by DharmaOCR Lite by DHARMA-AI S.A., licensed under the DharmaOCR Lite | |
| Noncommercial License 2026." | |
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