---
datasets:
- alexjerpelea/AroTranslate-rup-ron-dataset
language:
- ro
- en
license: cc-by-nc-4.0
tags:
- aromanian
- macedo-romanian
---
This model is an extension of [the first coherent Aromanian translator](https://huggingface.co/alexjerpelea/NLLB-aromanian-romanian-v1). <br>
It is a [NLLB-200-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) model fine-tuned for translating between any two languages out of: Aromanian, Romanian & English, using this [dataset](https://huggingface.co/datasets/alexjerpelea/aromanian-romanian-MT-corpus), which was artificially extended with Google Translate API.

Read more about AroTranslate at [this GitHub repository](https://github.com/lolismek/AroTranslate.git). 

We present the following results:
|  | ron -> rup | rup -> ron | rup -> eng | eng -> rup | ron -> eng | eng -> ron
|:----|:-----|:-----|:----|:-----|:-----|:-----|
|   BLEU  |  33.18  | 54.36 |  51.25 | 25.16 | 66.96 | 52.16
|   ChrF2++  |  59.47   |  68.54  | 66.13 | 52.68 | 78.84 | 70.34


Note: 
* As Aromanian does not have a standard writing system, please see code below for text normalization.
* This model was trained for production, being able to handle absence of diacritics. We do however recommend using them. 

How to use the model:
```py
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, NllbTokenizer
import re

# load model and tokenizer:
model = AutoModelForSeq2SeqLM.from_pretrained('alexjerpelea/NLLB-aromanian-romanian-english')
tokenizer = tokenizer = AutoTokenizer.from_pretrained('alexjerpelea/NLLB-aromanian-romanian-english')

# translate function:
def translate(
    text, src_lang='ron_Latn', tgt_lang='rup_Latn',
    a=32, b=3, max_input_length=1024, num_beams=4, **kwargs
):
    tokenizer.src_lang = src_lang
    tokenizer.tgt_lang = tgt_lang
    inputs = tokenizer(
        text, return_tensors='pt', padding=True, truncation=True,
        max_length=max_input_length
    )
    model.eval()
    result = model.generate(
        **inputs.to(model.device),
        forced_bos_token_id=tokenizer.convert_tokens_to_ids(tgt_lang),
        max_new_tokens=int(a + b * inputs.input_ids.shape[1]),
        num_beams=num_beams, **kwargs
    )
    return tokenizer.batch_decode(result, skip_special_tokens=True)


def clean_text(text, lang):
    if isinstance(text, float):
        return text

    # consecutive spaces
    text = re.sub(r'\s+', ' ', text).strip()
    # old romanian î in the middle of the word
    text = re.sub(r'(?<=\w)î(?=\w)', 'â', text)

    if lang == 'ron':
        text = text.replace('Ş', 'Ș')
        text = text.replace('ş', 'ș')
        text = text.replace('Ţ', 'Ț')
        text = text.replace('ţ', 'ț')
    else:
        text = text.replace('ş', 'sh')
        text = text.replace('ș', 'sh')
        text = text.replace('ţ', 'ts')
        text = text.replace('ț', 'ts')
        text = text.replace('Ş', 'Sh')
        text = text.replace('Ș', 'Sh')
        text = text.replace('Ţ', 'Ts')
        text = text.replace('Ț', 'Ts')

        text = text.replace('ľ', 'lj')
        text = text.replace('Ľ', 'L')

        text = text.replace("l'", "lj")
        text = text.replace("l’", "lj")
        text = text.replace("L'", "Lj")
        text = text.replace("L’", "Lj")

        text = text.replace('ḑ', 'dz')
        text = text.replace('Ḑ', 'dz')
        text = text.replace('ḍ', 'dz')
        text = text.replace('Ḍ', 'Dz')

        # TODO: add n'
        text = text.replace('ń', 'nj')
        text = text.replace('Ń', 'Nj')
        text = text.replace('ñ', 'nj')
        text = text.replace('Ñ', 'Nj')

        text = text.replace('ă', 'ã')
        text = text.replace('Â', 'Ã')
        text = text.replace('â', 'ã')
        text = text.replace('Ă', 'Ã')
        text = text.replace('á', 'ã')
        text = text.replace('à', 'ã')
        text = text.replace('Á', 'Ã')
        text = text.replace('À', 'Ã')

        text = text.replace('Î', 'Ã')
        text = text.replace('î', 'ã')

        # weird foreign characters
        text = text.replace('ŭ', 'u')
        text = text.replace('ς', 'c')
        text = text.replace('é', 'e')
        text = text.replace('í', 'i')
        text = text.replace('ū', 'u')
        text = text.replace('ì', 'i')
        text = text.replace('ā', 'a')
        text = text.replace('ĭ', 'i')
        text = text.replace('γ', 'y')
        text = text.replace('ï', 'i')
        text = text.replace('ó', 'o')
        text = text.replace('θ', 'O')

    # for both languages:
    text = text.replace('—', '-')
    text = text.replace('–', '-')
    text = text.replace('…', '...')
    text = text.replace('*', '')
    text = text.replace('<', '')
    text = text.replace('>', '')

    text = text.replace('„', '"')
    text = text.replace('”', '"')
    text = text.replace('“', '"')
    text = text.replace('”', '"')

    text = text.replace('\xa0', '')
    text = text.replace('\ufeff', '')
    text = text.replace('\n', '') 

    return text

# Aromanian to Romanian:
t = '''Trã atsea cãdzu pri mare cripare, shi tutã dzua stãtea ãnvirinat.'''
t = clean_text(t, 'rup')
print(translate(t, 'rup_Latn', 'ron_Latn'))

# Romanian to Aromanian:
t = '''Apoi se opri puțin, o sorbi din ochi, o sărută și - când începu să scâncească, îi cântă iar:'''
t = clean_text(t, 'rup')
print(translate(t, 'rup_Latn', 'ron_Latn'))

# Aromanian to English:
t = '''Cã a ta boatsi e birbil ti suflitu a meu.'''
t = clean_text(t, 'rup')
print(translate(t, 'rup_Latn', 'eng_Latn'))

# English to Aromanian:
t = '''That your voice is the nightingale of my soul.'''
print(translate(t, 'eng_Latn', 'rup_Latn'))
```

## License
<a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>. When using this work, please mention its name as "AroTranslate" and the author.