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  An OCR model trained on the [GoogleBooks Dataset](https://huggingface.co/datasets/ta4tsering/Google_Books_datasets) using a CRNN architecture.
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  We use the following architecture identifiers:
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  - E: Easter2 (https://huggingface.co/BDRC/GoogleBooks_E_v1)
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- - C: CRNN
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- - T: TrOCR (forthcoming)
 
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  An OCR model trained on the [GoogleBooks Dataset](https://huggingface.co/datasets/ta4tsering/Google_Books_datasets) using a CRNN architecture.
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  We use the following architecture identifiers:
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  - E: Easter2 (https://huggingface.co/BDRC/GoogleBooks_E_v1)
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+ - C: CRNN (this model)
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+ - T: TrOCR -> version 1 ((https://huggingface.co/BDRC/GoogleBooks_T_v1)) and version 2 ((https://huggingface.co/BDRC/GoogleBooks_T_v2). Version two is the recommended checkpoint if you want to run inferences. It was trained a little longer using the same data distribution. We keep v1 in oder to evaluate the actual differences on the predictions.