liat_ml_roberta
RoBERTa trained on Wikipedia Dump.
How to install
Can use pip to install.
pip install liat_ml_roberta
How to use
The loaded models and configurations can be used in the same way as transformers.roberta.
from liat_ml_roberta import RoBERTaTokenizer
def main():
tokenizer = RoBERTaTokenizer.from_pretrained(version="en_20190121_m10000_v24000_base")
print(tokenizer.tokenize("This is a pen."))
config = RoBERTaConfig.from_pretrained("roberta_base_en_20190121_m10000_v24000_u125000")
model = RoBERTaModel.from_pretrained("roberta_base_en_20190121_m10000_v24000_u125000", config=config)
if __name__ == "__main__":
main()
Models
| name | lang | size | bpe merges | vocab size | updates | wikipedia version |
|---|---|---|---|---|---|---|
| roberta_base_ja_20190121_m10000_v24000_u125000 | ja | roberta-base | 10000 | 24000 | 125000 | 20190121 |
| roberta_base_ja_20190121_m10000_v24000_u500000 | ja | roberta-base | 10000 | 24000 | 500000 | 20190121 |
| roberta_base_en_20190121_m10000_v24000_u125000 | en | roberta-base | 10000 | 24000 | 125000 | 20190121 |
| roberta_base_en_20190121_m10000_v24000_u500000 | en | roberta-base | 10000 | 24000 | 500000 | 20190121 |
| roberta_base_fr_20190121_m10000_v24000_u500000 | fr | roberta-base | 10000 | 24000 | 500000 | 20190121 |
| roberta_base_de_20190121_m10000_v24000_u500000 | de | roberta-base | 10000 | 24000 | 500000 | 20190121 |
1 maintainer
Metadata
1 maintainer
Release files for liat-ml-roberta 1.1.5
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Source distribution (sdist)
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| liat_ml_roberta-1.1.5.tar.gz | 1.3 MB | Without provenance | Details for liat_ml_roberta-1.1.5.tar.gz |
Built distribution (wheel)
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| liat_ml_roberta-1.1.5-py3-none-any.whl | Python 3 | none | any | Details for liat_ml_roberta-1.1.5-py3-none-any.whl |
Total release size: 2.5 MB
Release files / liat_ml_roberta-1.1.5.tar.gz
| Download URL | liat_ml_roberta-1.1.5.tar.gz |
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| Download URL | liat_ml_roberta-1.1.5-py3-none-any.whl |
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| Size | 1.3 MB |
| Tags | Python 3 |
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