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  It addresses structural variability and semantic entanglement by using a hierarchical supervision training strategy and a semantic-decoupled tokenizer. Despite its small size, it achieves performance comparable to or better than much larger vision-language models.
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- ## Get Started with the UniRec
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Dependencies:
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  It addresses structural variability and semantic entanglement by using a hierarchical supervision training strategy and a semantic-decoupled tokenizer. Despite its small size, it achieves performance comparable to or better than much larger vision-language models.
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+ ## Get Started with ONNX
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+ ### Install OpenOCR and Dependencies:
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+ ```shell
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+ git clone https://github.com/Topdu/OpenOCR.git
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+ pip install onnxruntime
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+ cd OpenOCR
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+ huggingface-cli download topdu/unirec_0_1b_onnx --local-dir ./unirec_0_1b_onnx
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+ ```
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+ ### Inference
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+ ```shell
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+ python ./tools/depolyment/unirec_onnx/infer_onnx.py --image /path/to/image
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+ ```
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+ ## Get Started with Pytorch
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  ### Dependencies:
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