Merge branch 'main' of https://huggingface.co/keshan/sinhala-roberta-oscar into main

README.md

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+---
+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>.")
+
+```