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bert-base-ner-theseus-bg
rmihaylov/bert-base-ner-theseus-bg
bert-base-ner-theseus-bg is a token classification model from rmihaylov. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
Pretrained model on Bulgarian language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is cased: it does make a difference between bu…
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Apr 16, 2022
- Updated
- Apr 16, 2022
- SHA
- 7a790473
Model card
From the Hugging Face model README
BERT BASE (cased) finetuned on Bulgarian named-entity-recognition data
Pretrained model on Bulgarian language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is cased: it does make a difference between bulgarian and Bulgarian. The training data is Bulgarian text from OSCAR, Chitanka and Wikipedia.
It was finetuned on public named-entity-recognition Bulgarian data.
Then, it was compressed via progressive module replacing.
How to use
Here is how to use this model in PyTorch:
>>> from transformers import pipeline
>>>
>>> model = pipeline(
>>> 'ner',
>>> model='rmihaylov/bert-base-ner-theseus-bg',
>>> tokenizer='rmihaylov/bert-base-ner-theseus-bg',
>>> device=0,
>>> revision=None)
>>> output = model('Здравей, аз се казвам Иван.')
>>> print(output)
[{'end': 26,
'entity': 'B-PER',
'index': 6,
'score': 0.9937722,
'start': 21,
'word': '▁Иван'}]
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- bg
- Created
- Apr 16, 2022
- Updated
- Apr 16, 2022