
# 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
<!-- Provide a quick summary of what the model is/does. -->

## 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

<!-- Provide a longer summary of what this model is. -->

- **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]

<!--- **Repository:** [More Information Needed] -->
{"tags": ["Levantine Arabic", "Shami", "English", "Egyptian"]}
transformers pytorch marian text2text-generation Levantine Arabic Shami English Egyptian autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #marian #text2text-generation #Levantine Arabic #Shami #English #Egyptian #autotrain_compatible #endpoints_compatible #has_space #region-us 


# 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: URL
- Version w/o conditional generation (Levantine only): URL


## 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 (URL@URL)
- Model type: MarianMT Seq2Seq
- License: MIT
- Finetuned from model: Helsinki-NLP/opus-mt-ar-en[URL


# 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: URL
- Version w/o conditional generation (Levantine only): URL ## 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 (URL@URL)
- Model type: MarianMT Seq2Seq
- License: MIT
- Finetuned from model: Helsinki-NLP/opus-mt-ar-en[URL
TAGS
#transformers #pytorch #marian #text2text-generation #Levantine Arabic #Shami #English #Egyptian #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # 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: URL
- Version w/o conditional generation (Levantine only): URL ## 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 (URL@URL)
- Model type: MarianMT Seq2Seq
- License: MIT
- Finetuned from model: Helsinki-NLP/opus-mt-ar-en[URL
TAGS
#transformers #pytorch #marian #text2text-generation #Levantine Arabic #Shami #English #Egyptian #autotrain_compatible #endpoints_compatible #has_space #region-us 
# 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: URL
- Version w/o conditional generation (Levantine only): URL## 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 (URL@URL)
- Model type: MarianMT Seq2Seq
- License: MIT
- Finetuned from model: Helsinki-NLP/opus-mt-ar-en[URL