Image-Text-to-Text
MLX
Safetensors
unlimited-ocr
ax-engine
mlx-vlm
ocr
mxfp8
int8
apple-silicon
automatosx
conversational
8-bit precision
Instructions to use AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8 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("AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8") config = load_config("AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8") # 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
- Atomic Chat
| """Example: OCR a single image file.""" | |
| from unlimited_ocr import OCRPipeline | |
| # Initialize the pipeline (model loads lazily on first inference) | |
| pipeline = OCRPipeline( | |
| model_path="AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8", | |
| verbose=True, | |
| ) | |
| # --- Basic document OCR --- | |
| result = pipeline.run("your_document.jpg", format="text") | |
| print(result) | |
| # --- Markdown output --- | |
| result = pipeline.run("your_document.jpg", format="markdown", output_path="output.md") | |
| print("Saved to output.md") | |
| # --- With bounding boxes (grounding mode) --- | |
| result = pipeline.run("your_document.jpg", format="json", grounding=True) | |
| print(result) | |
| # --- With image preprocessing (deskew + contrast enhancement) --- | |
| result = pipeline.run("scanned_page.png", format="text", preprocess=True) | |
| print(result) | |
| # --- Different task types --- | |
| # "document" — general document parsing (default) | |
| # "markdown" — convert to markdown structure | |
| # "figure" — parse figures/diagrams | |
| # "free" — free-form OCR | |
| result = pipeline.run("table.png", task="markdown", format="markdown") | |
| print(result) | |
| # Clean up temporary files | |
| pipeline.cleanup() | |