How to use jmbarrancoidener/PaddleOCR-VL-1.6-mlx-8bit 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("jmbarrancoidener/PaddleOCR-VL-1.6-mlx-8bit") config = load_config("jmbarrancoidener/PaddleOCR-VL-1.6-mlx-8bit") # 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)
How to use jmbarrancoidener/PaddleOCR-VL-1.6-mlx-8bit with PaddleOCR:
# See https://www.paddleocr.ai/latest/version3.x/pipeline_usage/PaddleOCR-VL.html to installation from paddleocr import PaddleOCRVL pipeline = PaddleOCRVL(pipeline_version="jmbarrancoidener/PaddleOCR-VL-1.6-mlx-8bit") output = pipeline.predict("path/to/document_image.png") for res in output: res.print() res.save_to_json(save_path="output") res.save_to_markdown(save_path="output")
