---
license: cc-by-nc-4.0
language:
- ar
pipeline_tag: token-classification
datasets:
- guymorlan/levanti
- community-datasets/tashkeela
---

# Levanti Diacritizer

This model adds diacritics to raw text in Palestinian colloquial Arabic. 
The model is trained on a special subset of the Levanti dataset (to be released later).
The model is fine-tuned from Google's [CANINE-s](https://huggingface.co/google/canine-s) character level LM with a multi-label token classification head.
CANINE-s is first pre-trained on the Tashkeela dataset of classical Arabic diacritized text (after removing final diacritics from the text) and then trained for an additional 5 epochs on the diacritized subset of the Levanti dataset. 
Each token (letter) of the input is classified into 6 positive categories: Shadda, Fatha, Kasra, Damma and Sukun (see `model.config.id2label`). A multi-label model is used since a Shadda can accompany other diacritical marks.

# Transliterator
This model can be used in conjunction with [Levanti Transliterator](https://huggingface.co/guymorlan/levanti_diacritics2translit/), which transliterated diacritized text in Palestinian Arabic.

# Example Usage

```python
from transformers import CanineForTokenClassification, AutoTokenizer
model = CanineForTokenClassification.from_pretrained("guymorlan/levanti_arabic2diacritics")
tokenizer = AutoTokenizer.from_pretrained("guymorlan/levanti_arabic2diacritics")

label2diacritic = {0: 'ّ', 1: 'َ', 2: 'ِ', 3: 'ُ', 4: ''}

def arabic2diacritics(text, model, tokenizer):
    tokens = tokenizer(text, return_tensors="pt")
    preds = (model(**tokens).logits.sigmoid() > 0.5)[0]
    new_text = []
    for p, c in zip(preds, text):
        for i in range(1, 5):
            if p[i]:
                new_text.append(label2diacritic[i])
        # check shadda last
        if p[0]:
            new_text.append(label2diacritic[0])
        new_text.append(c)
    new_text = "".join(new_text)
    return new_text

text = "بديش اروح عالمدرسة بكرا"
arabic2diacritics(text, model, tokenizer)
```
```
```

# Attribution
Created by Guy Mor-Lan.<br>
Contact: guy.mor AT mail.huji.ac.il