Image-Text-to-Text
MLX
Safetensors
multilingual
deepseekocr
mlx-vlm
quantized
apple-silicon
deepseek-ocr
ocr
vision-language
multimodal
document-parsing
conversational
8-bit precision
Instructions to use sahilchachra/unlimited-ocr-8bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sahilchachra/unlimited-ocr-8bit-mlx 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("sahilchachra/unlimited-ocr-8bit-mlx") config = load_config("sahilchachra/unlimited-ocr-8bit-mlx") # 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 Settings
- LM Studio
| {% for message in messages %}{% if message['role'] == 'user' %}{% elif message['role'] == 'assistant' %}{% endif %}{{message['content']}} {% endfor %}{% if add_generation_prompt %}{% endif %} |