Image Feature Extraction
Transformers
Safetensors
monkeyocrv2_vitae_encoder
feature-extraction
custom_code
Instructions to use zenosai/MonkeyOCRv2-AS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenosai/MonkeyOCRv2-AS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="zenosai/MonkeyOCRv2-AS", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zenosai/MonkeyOCRv2-AS", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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Our model supports robust document parsing in real-world scenarios across 17 languages, including Simplified Chinese (ZH), Traditional Chinese (ZH-T), English (EN), Arabic (AR), German (DE), Spanish (ES), French (FR), Hindi (HI), Indonesian (ID), Italian (IT), Japanese (JP), Korean (KO), Dutch (NL), Portuguese (PT), Russian (RU), Thai (TH), and Vietnamese (VI).
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<img src="https://github.com/Yuliang-Liu/MonkeyOCRv2/blob/main/asserts/
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## Evaluation Results
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Our model supports robust document parsing in real-world scenarios across 17 languages, including Simplified Chinese (ZH), Traditional Chinese (ZH-T), English (EN), Arabic (AR), German (DE), Spanish (ES), French (FR), Hindi (HI), Indonesian (ID), Italian (IT), Japanese (JP), Korean (KO), Dutch (NL), Portuguese (PT), Russian (RU), Thai (TH), and Vietnamese (VI).
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<img src="https://github.com/Yuliang-Liu/MonkeyOCRv2/blob/main/asserts/text_detection.png?raw=true" width="600"/>
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## Evaluation Results
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