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@@ -35,6 +35,8 @@ Training images were resized with a fixed height of 128 pixels, keeping the orig
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  | val | 2,286 |
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  | test | 1,793 |
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  ## Evaluation results
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  The model achieves the following results:
@@ -44,8 +46,6 @@ The model achieves the following results:
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  | test | no | 7.94 | 24.04 | 1,793 |
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  | test | yes | 6.55 | 18.20 | 1,793 |
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- An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the NorHand v1 training set.
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-
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  ## How to use?
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  Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model.
 
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  | val | 2,286 |
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  | test | 1,793 |
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+ An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the NorHand v1 training set.
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+
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  ## Evaluation results
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  The model achieves the following results:
 
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  | test | no | 7.94 | 24.04 | 1,793 |
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  | test | yes | 6.55 | 18.20 | 1,793 |
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  ## How to use?
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  Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model.