Create README.md

README.md

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+---
+inference: false
+language:
+- bg
+license: mit
+datasets:
+- oscar
+- chitanka
+- wikipedia
+tags:
+- torch
+---
+
+# 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](https://arxiv.org/abs/1810.04805) and first released in
+[this repository](https://github.com/google-research/bert). This model is cased: it does make a difference
+between bulgarian and Bulgarian. The training data is Bulgarian text from [OSCAR](https://oscar-corpus.com/post/oscar-2019/), [Chitanka](https://chitanka.info/) and [Wikipedia](https://bg.wikipedia.org/).
+
+It was finetuned on public named-entity-recognition Bulgarian data.
+
+Then, it was compressed via [progressive module replacing](https://arxiv.org/abs/2002.02925).
+
+### How to use
+
+Here is how to use this model in PyTorch:
+
+```python
+>>> 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'}]
+```