Image-Text-to-Text
MLX
Safetensors
PaddleOCR
English
Chinese
multilingual
paddleocr_vl
ERNIE4.5
PaddlePaddle
image-to-text
ocr
conversational
custom_code
4-bit precision
Instructions to use huggingfinger0/PaddleOCR-VL-1.5-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use huggingfinger0/PaddleOCR-VL-1.5-4bit 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("huggingfinger0/PaddleOCR-VL-1.5-4bit") config = load_config("huggingfinger0/PaddleOCR-VL-1.5-4bit") # 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) - PaddleOCR
How to use huggingfinger0/PaddleOCR-VL-1.5-4bit with PaddleOCR:
# Please refer to the document for information on how to use the model. # https://paddlepaddle.github.io/PaddleOCR/latest/en/version3.x/module_usage/module_overview.html
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_paddleocr_vl.PaddleOCRVLImageProcessor", | |
| "AutoProcessor": "processing_paddleocr_vl.PaddleOCRVLProcessor" | |
| }, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "PaddleOCRVLImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "max_pixels": 1003520, | |
| "merge_size": 2, | |
| "min_pixels": 112896, | |
| "patch_size": 14, | |
| "processor_class": "PaddleOCRVLProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "temporal_patch_size": 1 | |
| } | |