Image-Text-to-Text
PaddleOCR
Safetensors
English
Chinese
multilingual
paddleocr_vl
ERNIE4.5
PaddlePaddle
image-to-text
ocr
document-parse
layout
table
formula
chart
conversational
custom_code
Eval Results
Instructions to use PaddlePaddle/PaddleOCR-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PaddleOCR
How to use PaddlePaddle/PaddleOCR-VL 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="v1") 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") - Notebooks
- Google Colab
- Kaggle
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README.md
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## PaddleOCR-VL-0.9B Usage with transformers
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Currently, we support inference using the PaddleOCR-VL-0.9B model with the `transformers` library, which can recognize texts, formulas, tables, and chart elements. In the future, we plan to support full document parsing inference with `transformers`. Below is a simple script we provide to support inference using the PaddleOCR-VL-0.9B model with `transformers`.
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```python
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## PaddleOCR-VL-0.9B Usage with transformers
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Currently, we support inference using the PaddleOCR-VL-0.9B model with the `transformers` library, which can recognize texts, formulas, tables, and chart elements. In the future, we plan to support full document parsing inference with `transformers`. Below is a simple script we provide to support inference using the PaddleOCR-VL-0.9B model with `transformers`.
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> [!NOTE]
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> Note: We currently recommend using the official method for inference, as it is faster and supports page-level document parsing. The example code below only supports element-level recognition.
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```python
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