zakaCH/Algerian-Darija-Translator

🇩🇿🇲🇦🇹🇳 Maghrebi Darija to English Translator (V3 Ultimate)

This model is a state-of-the-art fine-tuned version of facebook/nllb-200-1.3B, specifically designed to translate Maghrebi Arabic Dialects (Algerian, Moroccan, and Tunisian Darija) into English.

🚀 Model Details

• Base Model: NLLB-200-1.3B (Meta)
• Training Data: Over 120,000 highly curated parallel sentences, including daily conversations, social media slang, and deep cultural proverbs.
• Hardware Used: Dual T4 GPUs (Kaggle)
• Developer: Zakaria CH

🧠 Why this model?

Standard translation models often fail at Maghrebi dialects, usually defaulting to Modern Standard Arabic (MSA) literal translations. This model was explicitly trained to understand the context and slang of the Maghreb region (e.g., translating "قتلو" contextually as "I told him" instead of the literal "I killed him").

💻 How to use in Python

`python from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model_name = "zakaCH/Algerian-Darija-Translator" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

text = "واش يا خويا كاش جديد في الحومة؟" tokenizer.src_lang = "arb_Arab" inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, forced_bos_token_id=tokenizer.convert_tokens_to_ids("eng_Latn"), max_length=128) print(tokenizer.batch_decode(outputs, skip_special_tokens=True)[0])

Output: "What's up bro, any news in the neighborhood?"