Update README.md

README.md

@@ -29,8 +29,8 @@ The model has been trained using the PyLaia library on the [NewsEye / READ OCR t
 
 Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
 
-| split | N lines |
-| ----- | ------: |
+| set | lines |
+| :---- | ------: |
 | train |  52,834 |
 | val   |   4,667 |
 
@@ -40,22 +40,26 @@ An external 6-gram character language model can be used to improve recognition.
 
 The model achieves the following results:
 
-| set   | Language model | CER (%)    | WER (%) | N lines   |
+| set   | Language model | CER (%)    | WER (%) | lines   |
 |:------|:---------------| ----------:| -------:|----------:|
 | val   | no             |  1.82      |   7.77  |     4,667 |
 | val   | yes            |  1.77      |   7.01  |     4,667 |
 
 ## How to use?
 
-Please refer to the [documentation](https://atr.pages.teklia.com/pylaia/).
+Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model.
 
 ## Cite us!
 
 ```bibtex
-@inproceedings{pylaia-lib,
-    author = "Tarride, Solène and Schneider, Yoann and Generali, Marie and Boillet, Melodie and Abadie, Bastien and Kermorvant, Christopher",
-    title = "Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library",
-    booktitle = "Submitted at ICDAR2024",
-    year = "2024"
+@inproceedings{pylaia2024,
+    author = {Tarride, Solène and Schneider, Yoann and Generali-Lince, Marie and Boillet, Mélodie and Abadie, Bastien and Kermorvant, Christopher},
+    title = {{Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library}},
+    booktitle = {Document Analysis and Recognition - ICDAR 2024},
+    year = {2024},
+    publisher = {Springer Nature Switzerland},
+    address = {Cham},
+    pages = {387--404},
+    isbn = {978-3-031-70549-6}
 }
 ```