readme: # Description:
  
  This is a smaller per-trained model on Sinhalese Language using Masked Language Modeling(MLM). And the model is trained on Oscar Sinhala dataset.
  
  # How to Use:
  The model can be used directly with a pipeline for masked language modeling:
  ```python
  >>> from transformers import AutoTokenizer, AutoModelForMaskedLM, pipeline
  >>> tokenizer = AutoTokenizer.from_pretrained("d42kw01f/Sinhala-RoBERTa")
  >>> model = AutoModelForMaskedLM.from_pretrained("d42kw01f/Sinhala-RoBERTa")
  >>> fill_mask = pipeline('fill-mask', model=model, tokenizer=tokenizer)
  >>> fill_mask("මම ගෙදර <mask>.")
  [{'score': 0.1822454035282135,
    'sequence': 'මම ගෙදර ආව.',
    'token': 701,
    'token_str': ' ආව'},
   {'score': 0.10513380169868469,
    'sequence': 'මම ගෙදර ය.',
    'token': 310,
    'token_str': ' ය'},
   {'score': 0.06417194753885269,
    'sequence': 'මම ගෙදර එක.',
    'token': 328,
    'token_str': ' එක'},
   {'score': 0.05026362091302872,
    'sequence': 'මම ගෙදර ඇත.',
    'token': 330,
    'token_str': ' ඇත'},
   {'score': 0.029960114508867264,
    'sequence': 'මම ගෙදර යනව.',
    'token': 834,
    'token_str': ' යනව'}]
    ```