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

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+ ---
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+ language: si
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+ tags:
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+ - oscar
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+ - Sinhala
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+ - roberta
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+ - fill-mask
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+ widget:
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+ - text: "මම සිංහල භාෂාව <mask>"
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+ datasets:
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+ - oscar
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+ ---
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+ ### Overview
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+
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+ 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.
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+
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+ ## Model Specification
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+
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+
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+ The model chosen for training is [Roberta](https://arxiv.org/abs/1907.11692) with the following specifications:
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+ 1. vocab_size=50265
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+ 2. max_position_embeddings=514
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+ 3. num_attention_heads=12
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+ 4. num_hidden_layers=12
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+ 5. type_vocab_size=1
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+
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+ ## How to Use
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+ You can use this model directly with a pipeline for masked language modeling:
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+
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+ ```py
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+ from transformers import AutoTokenizer, AutoModelWithLMHead, pipeline
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+
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+ model = AutoModelWithLMHead.from_pretrained("keshan/sinhala-roberta-oscar")
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+ tokenizer = AutoTokenizer.from_pretrained("keshan/sinhala-roberta-oscar")
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+
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+ fill_mask = pipeline('fill-mask', model=model, tokenizer=tokenizer)
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+
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+ fill_mask("මම ගෙදර <mask>.")
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+
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+ ```