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The dataset consists of synthetic OCR training content featuring a font distribution ratio of approximately 60% serif, 32% sans-serif, and 8% monospace typefaces. It is designed to train optical character recognition models across diverse typographical styles, balancing common serif/sans-serif combinations with a smaller proportion of fixed-width fonts for specialized applications.
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