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README.md
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- text: "Budi adalah anak yang pintar karena ia suka <mask>."
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---
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-
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## How to Use
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### As Masked Language Model
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```python
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from transformers import pipeline
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pretrained_name = "akahana/roberta-base-indonesia"
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fill_mask = pipeline(
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"fill-mask",
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model=pretrained_name,
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tokenizer=pretrained_name
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)
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fill_mask("Budi adalah anak yang pintar karena ia suka <mask>.")
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```
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### Feature Extraction in PyTorch
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```python
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from transformers import RobertaModel, RobertaTokenizerFast
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pretrained_name = "akahana/roberta-base-indonesia"
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model = RobertaModel.from_pretrained(pretrained_name)
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tokenizer = RobertaTokenizerFast.from_pretrained(pretrained_name)
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prompt = "Budi adalah anak yang pintar karena ia suka belajar."
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encoded_input = tokenizer(prompt, return_tensors='pt')
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output = model(**encoded_input)
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- text: "Budi adalah anak yang pintar karena ia suka <mask>."
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---
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# Indonesian RoBERTa Base
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## How to Use
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### As Masked Language Model
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```python
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from transformers import pipeline
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+
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pretrained_name = "akahana/roberta-base-indonesia"
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+
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fill_mask = pipeline(
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"fill-mask",
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model=pretrained_name,
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tokenizer=pretrained_name
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)
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+
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fill_mask("Budi adalah anak yang pintar karena ia suka <mask>.")
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```
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### Feature Extraction in PyTorch
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```python
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from transformers import RobertaModel, RobertaTokenizerFast
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+
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pretrained_name = "akahana/roberta-base-indonesia"
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model = RobertaModel.from_pretrained(pretrained_name)
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tokenizer = RobertaTokenizerFast.from_pretrained(pretrained_name)
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prompt = "Budi adalah anak yang pintar karena ia suka belajar."
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encoded_input = tokenizer(prompt, return_tensors='pt')
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output = model(**encoded_input)
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