---
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- atr
- htr
- ocr
- historical
- handwritten
metrics:
- CER
- WER
language:
- fr
base_model: Teklia/pylaia-norhand-v3
datasets:
- Teklia/PELLET-Casimir-Marius-line
pipeline_tag: image-to-text
---

# PyLaia - PELLET Casimir Marius - Line level

This model performs Handwritten Text Recognition in French.

## Model description

The model has been trained using the PyLaia library on the [PELLET Casimir Marius - Line level](Teklia/PELLET-Casimir-Marius-line) dataset.

Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.

| set   | lines |
| :---- | ----: |
| train |   842 |
| val   |   125 |
| test  |   122 |

## Evaluation results

The model achieves the following results:

| set   | CER (%) | WER (%) | text_line |
| :---- | ------: | ------: | --------: |
| train |       0 |       0 |       842 |
| val   |       0 |       0 |       125 |
| test  |       0 |       0 |       122 |

## How to use?

Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model.

## Cite us!


```bibtex
@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}
}
```

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