Image-Text-to-Text
MLX
Safetensors
mistral3
ocr
document-understanding
vision-language
pdf
tables
forms
conversational
4-bit precision
Instructions to use humpf/LightOnOCR-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use humpf/LightOnOCR-4bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("humpf/LightOnOCR-4bit") config = load_config("humpf/LightOnOCR-4bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
| {% set image_count = namespace(value=0) %} | |
| {% for message in messages %} | |
| {% if loop.first and message['role'] != 'system' %} | |
| <|im_start|>system<|im_end|> | |
| {% endif %} | |
| <|im_start|>{{ message['role'] }} | |
| {% if message['content'] is string %} | |
| {{ message['content'] }}<|im_end|> | |
| {% else %} | |
| {% for content in message['content'] %} | |
| {% if content['type'] == 'image' or 'image' in content or 'image_url' in content %} | |
| {% set image_count.value = image_count.value + 1 %} | |
| {% if add_vision_id %} | |
| Picture {{ image_count.value }}: | |
| {% endif -%} | |
| <|image_pad|> | |
| {%- elif 'text' in content %} | |
| {{ content['text'] }} | |
| {% endif %} | |
| {% endfor %} | |
| <|im_end|> | |
| {% endif %} | |
| {% endfor %} | |
| {% if add_generation_prompt %} | |
| <|im_start|>assistant | |
| {% endif %} |