|
--- |
|
language: |
|
- fa |
|
- multilingual |
|
thumbnail: "https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg" |
|
tags: |
|
- machine-translation |
|
- mt5 |
|
- persian |
|
- farsi |
|
license: "CC BY-NC-SA 4.0" |
|
datasets: |
|
- parsinlu |
|
metrics: |
|
- sacrebleu |
|
--- |
|
|
|
# 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?") |
|
``` |
|
|
|
|
|
|
|
For more details, visit this page: https://github.com/persiannlp/parsinlu/ |
|
|
