### How to use

You can use this model directly with a pipeline:


```python
from transformers import AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("shihab17/bengali-bn-to-en")
model = AutoModelForSeq2SeqLM.from_pretrained("shihab17/bengali-bn-to-en")

sentence = 'ম্যাচ শেষে পুরস্কার বিতরণের মঞ্চে তামিমের মুখে মোস্তাফিজের প্রশংসা শোনা গেল'

translator = pipeline("translation_bn_to_en", model=model, tokenizer=tokenizer)
output = translator(sentence)
print(output)
```
{"language": ["bn"], "library_name": "transformers", "pipeline_tag": "translation"}
transformers pytorch tensorboard safetensors marian text2text-generation translation bn autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #marian #text2text-generation #translation #bn #autotrain_compatible #endpoints_compatible #region-us 

### How to use

You can use this model directly with a pipeline:



### How to use

You can use this model directly with a pipeline:
TAGS
#transformers #pytorch #tensorboard #safetensors #marian #text2text-generation #translation #bn #autotrain_compatible #endpoints_compatible #region-us 
 ### How to use

You can use this model directly with a pipeline: