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Indonesian RoBERTa Base

How to Use

As Masked Language Model

from transformers import pipeline

pretrained_name = "akahana/roberta-base-indonesia"

fill_mask = pipeline(
    "fill-mask",
    model=pretrained_name,
    tokenizer=pretrained_name
)

fill_mask("Gajah <mask> sedang makan di kebun binatang.")

Feature Extraction in PyTorch

from transformers import RobertaModel, RobertaTokenizerFast

pretrained_name = "akahana/roberta-base-indonesia"
model = RobertaModel.from_pretrained(pretrained_name)
tokenizer = RobertaTokenizerFast.from_pretrained(pretrained_name)

prompt = "Gajah <mask> sedang makan di kebun binatang."
encoded_input = tokenizer(prompt, return_tensors='pt')
output = model(**encoded_input)
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Model size
125M params
Tensor type
I64
·
F32
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Dataset used to train akahana/roberta-base-indonesia