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English2Dialect
This model generates translations from English to colloquial Arabic, conditioning the translations on dialect. Supported dialects are: Palestinian/Jordanian, Syrian, Lebanese and Egyptian. Dialect is specified via the first input token which should be either P/S/L/E.
For example, to translate to Palestinian/Jordanian, use the input:
P What time is it now?
And for Syrian:
S What time is it now?
- Demo: https://huggingface.co/spaces/guymorlan/English2Shami
- Version w/o conditional generation (Levantine only): https://huggingface.co/guymorlan/English2Shami
Training Data
The model was trained by fine-tuning the opus-mt-ar-en (MSA to English) model on ~85K parallel sentences in four dialects of colloquial Arabic.
Model Description
- Developed by: Guy Mor-Lan (guy.mor@mail.huji.ac.il)
- Model type: MarianMT Seq2Seq
- License: MIT
- Finetuned from model: Helsinki-NLP/opus-mt-ar-en[https://huggingface.co/Helsinki-NLP/opus-mt-ar-en]
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("guymorlan/English2Dialect") model = AutoModelForSeq2SeqLM.from_pretrained("guymorlan/English2Dialect")