readme: ---
  inference: false
  language:
  - bg
  license: mit
  datasets:
  - oscar
  - chitanka
  - wikipedia
  tags:
  - torch
  ---
  
  # ROBERTA-TO-ROBERTA EncoderDecoder with Shared Weights
  
  This model was introduced in [this paper](https://arxiv.org/pdf/1907.12461.pdf). 
  
  ## Model description
  
  The training data is private English-Bulgarian parallel data. 
  
  ## Intended uses & limitations
  
  You can use the raw model for translation from English to Bulgarian.
  
  ### How to use
  
  Here is how to use this model in PyTorch:
  
  ```python
  >>> from transformers import EncoderDecoderModel, XLMRobertaTokenizer
  >>>
  >>> model_id = "rmihaylov/roberta2roberta-shared-nmt-bg"
  >>> model = EncoderDecoderModel.from_pretrained(model_id)
  >>> model.encoder.pooler = None
  >>> tokenizer = XLMRobertaTokenizer.from_pretrained(model_id)
  >>>
  >>> text = """
  Others were photographed ransacking the building, smiling while posing with congressional items such as House Speaker Nancy Pelosi's lectern or at her staffer's desk, or publicly bragged about the crowd's violent and destructive joyride.
  """
  >>>
  >>> inputs = tokenizer.encode_plus(text, max_length=100, return_tensors='pt', truncation=True)
  >>> 
  >>> translation = model.generate(**inputs, 
  >>>     max_length=100, 
  >>>     num_beams=4, 
  >>>     do_sample=True,
  >>>     num_return_sequences=1, 
  >>>     top_p=0.95,
  >>>     decoder_start_token_id=tokenizer.bos_token_id)
  >>>
  >>> print([tokenizer.decode(g.tolist(), skip_special_tokens=True) for g in translation])
  
  ['Други бяха заснети да бягат из сградата, усмихвайки се, докато се представят с конгресни предмети, като например лекцията на председателя на парламента Нанси Пелози или на бюрото на нейния служител, или публично се хвалят за насилието и разрушителната радост на тълпата.']
  ```
  