readme: ---
  language: si
  tags:
  - oscar
  - Sinhala
  - roberta
  - fill-mask
  widget:
  - text: "මම සිංහල භාෂාව <mask>"
  datasets:
  - oscar
  ---
  ### Overview
  
  This is a slightly smaller model trained on [OSCAR](https://oscar-corpus.com/) Sinhala dedup dataset. As Sinhala is one of those low resource languages, there are only a handful of models been trained. So, this would be a great place to start training for more downstream tasks. 
  
  ## Model Specification
  
  
  The model chosen for training is [Roberta](https://arxiv.org/abs/1907.11692) with the following specifications:
   1. vocab_size=50265
   2. max_position_embeddings=514
   3. num_attention_heads=12
   4. num_hidden_layers=12
   5. type_vocab_size=1
   
  ## How to Use
  You can use this model directly with a pipeline for masked language modeling:
  
  ```py
  from transformers import AutoTokenizer, AutoModelWithLMHead, pipeline
  
  model = AutoModelWithLMHead.from_pretrained("keshan/sinhala-roberta-oscar")
  tokenizer = AutoTokenizer.from_pretrained("keshan/sinhala-roberta-oscar")
  
  fill_mask = pipeline('fill-mask', model=model, tokenizer=tokenizer)
  
  fill_mask("මම ගෙදර <mask>.")
  
  ```
  