
# Machine Translation (ترجمه‌ی ماشینی)

This is an mT5-based model for machine translation (English -> Persian). 
Here is an example of how you can run this model: 

```python 
from transformers import MT5ForConditionalGeneration, MT5Tokenizer

model_size = "large"
model_name = f"persiannlp/mt5-{model_size}-parsinlu-translation_en_fa"
tokenizer = MT5Tokenizer.from_pretrained(model_name)
model = MT5ForConditionalGeneration.from_pretrained(model_name)


def run_model(input_string, **generator_args):
    input_ids = tokenizer.encode(input_string, return_tensors="pt")
    res = model.generate(input_ids, **generator_args)
    output = tokenizer.batch_decode(res, skip_special_tokens=True)
    print(output)
    return output


run_model("Praise be to Allah, the Cherisher and Sustainer of the worlds;")
run_model("shrouds herself in white and walks penitentially disguised as brotherly love through factories and parliaments; offers help, but desires power;")
run_model("He thanked all fellow bloggers and organizations that showed support.")
run_model("Races are held between April and December at the Veliefendi Hippodrome near Bakerky, 15 km (9 miles) west of Istanbul.")
run_model("I want to pursue PhD in Computer Science about social network,what is the open problem in social networks?")
```
which should output: 
```
['خدا را شکر که آفریننده و نگهدار جهان است.']
['خود را با کفن سفید می پوشد و به شکل برادرانه ای در']
['او از همه ی وبلاگ نویسان و سازمان هایی که از او حمایت کردند']
['مسابقات بین آوریل و دسامبر در فرودگاه والی عبدین نزدیک بی']
['من می خواهم پایان نامه دکتری را در رشته علوم کامپیوتر در']
```


For more details, visit this page: https://github.com/persiannlp/parsinlu/ 

{"language": ["fa", "multilingual"], "license": "cc-by-nc-sa-4.0", "tags": ["machine-translation", "mt5", "persian", "farsi"], "datasets": ["parsinlu"], "metrics": ["sacrebleu"], "thumbnail": "https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg"}
transformers pytorch mt5 text2text-generation machine-translation persian farsi fa multilingual dataset:parsinlu license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #machine-translation #persian #farsi #fa #multilingual #dataset-parsinlu #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 


# Machine Translation (ترجمه‌ی ماشینی)

This is an mT5-based model for machine translation (English -> Persian). 
Here is an example of how you can run this model: 


which should output: 



For more details, visit this page: URL 

# Machine Translation (ترجمه‌ی ماشینی)

This is an mT5-based model for machine translation (English -> Persian). 
Here is an example of how you can run this model: 


which should output: 



For more details, visit this page: URL
TAGS
#transformers #pytorch #mt5 #text2text-generation #machine-translation #persian #farsi #fa #multilingual #dataset-parsinlu #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # Machine Translation (ترجمه‌ی ماشینی)

This is an mT5-based model for machine translation (English -> Persian). 
Here is an example of how you can run this model: 


which should output: 



For more details, visit this page: URL
TAGS
#transformers #pytorch #mt5 #text2text-generation #machine-translation #persian #farsi #fa #multilingual #dataset-parsinlu #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
# Machine Translation (ترجمه‌ی ماشینی)

This is an mT5-based model for machine translation (English -> Persian). 
Here is an example of how you can run this model: 


which should output: 



For more details, visit this page: URL