SinhalaBERTo / README.md
---
language: si
tags:
- SinhalaBERTo
- Sinhala
- roberta
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=52000
2. max_position_embeddings=514
3. num_attention_heads=12
4. num_hidden_layers=6
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/SinhalaBERTo")
tokenizer = AutoTokenizer.from_pretrained("keshan/SinhalaBERTo")
fill_mask = pipeline('fill-mask', model=model, tokenizer=tokenizer)
fill_mask("මම ගෙදර <mask>.")
```