| # 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'}] | |
| ``` |