Create README.md

README.md

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+---
+inference: false
+language:
+- bg
+license: mit
+datasets:
+- oscar
+- chitanka
+- wikipedia
+tags:
+- torch
+---
+
+# BERT BASE (cased)
+
+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/).
+
+### How to use
+
+Here is how to use this model in PyTorch:
+
+```python
+>>> from transformers import pipeline
+>>> 
+>>> model = pipeline(
+>>>     'fill-mask',
+>>>     model='rmihaylov/bert-base-bg',
+>>>     tokenizer='rmihaylov/bert-base-bg',
+>>>     device=0,
+>>>     revision=None)
+>>> output = model("София е [MASK] на България.")
+>>> print(output)
+
+[{'score': 0.12665307521820068,
+  'sequence': 'София е  столица на България.',
+  'token': 2659,
+  'token_str': 'столица'},
+ {'score': 0.07470757514238358,
+  'sequence': 'София е Перлата на България.',
+  'token': 102146,
+  'token_str': 'Перлата'},
+ {'score': 0.06786204129457474,
+  'sequence': 'София е  Столицата на България.',
+  'token': 45495,
+  'token_str': 'Столицата'},
+ {'score': 0.05533991754055023,
+  'sequence': 'София е  Столица на България.',
+  'token': 100524,
+  'token_str': 'Столица'},
+ {'score': 0.05485989898443222,
+  'sequence': 'София е  столицата на България.',
+  'token': 2294,
+  'token_str': 'столицата'}]