UniRec-0.1B is a unified recognition model with only 0.1B parameters, designed for high-accuracy and efficient recognition of plain text (words, lines, paragraphs), mathematical formulas (single-line, multi-line), and mixed content in both Chinese and English. 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. - PyTorch version >= 1.13.0 - Python version >= 3.7 It is recommended to organize your working directory as follows: Download the UniRec40M dataset from Hugging Face Run the…
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Ivan
ryanivan
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