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SinhalaBERTo
keshan/SinhalaBERTo
SinhalaBERTo is a fill-mask model from keshan. Use it when you need the model to fill a missing word. It is set up for transformers.
This is a slightly smaller model trained on OSCAR 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 tra…
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From the Hugging Face model README
Overview
This is a slightly smaller model trained on OSCAR 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 with the following specifications:
- vocab_size=52000
- max_position_embeddings=514
- num_attention_heads=12
- num_hidden_layers=6
- type_vocab_size=1
How to Use
You can use this model directly with a pipeline for masked language modeling:
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>.")
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- Languages
- si
- Created
- Mar 2, 2022
- Updated
- Mar 19, 2023