magistermilitum
/

tridis_HTR

vision-encoder-decoder

image-text-to-text

handwritten-text-recognition

Inference Endpoints

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magistermilitum commited on May 23

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@@ -66,7 +66,7 @@ During evaluation, the model showed an accuracy of 94.3% on the validation set a
 and a WER of about 0.14 to 0.26 respectively, which is about 30% lower compared to CRNN+CTC solutions trained on the same corpora.
 ### Other formats
-A CRNN+CTC version of this model trained on Kraken 4.0 using the same gold-standard annotation is available in Zenodo:
 Torres Aguilar, S., & Jolivet, V. (2024). TRIDIS: HTR model for Multilingual Medieval and Early Modern Documentary Manuscripts (11th-16th) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10800223

 and a WER of about 0.14 to 0.26 respectively, which is about 30% lower compared to CRNN+CTC solutions trained on the same corpora.
 ### Other formats
+A CRNN+CTC version of this model trained on Kraken 4.0 (https://github.com/mittagessen/kraken) using the same gold-standard annotation is available in Zenodo:
 Torres Aguilar, S., & Jolivet, V. (2024). TRIDIS: HTR model for Multilingual Medieval and Early Modern Documentary Manuscripts (11th-16th) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10800223