README.md

---
inference: false
language:
- bg
license: mit
datasets:
- oscar
- chitanka
- wikipedia
tags:
- torch
---

# BERT BASE (cased) finetuned on Bulgarian squad 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 private squad 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(
>>>     'question-answering',
>>>     model='rmihaylov/bert-base-squad-theseus-bg',
>>>     tokenizer='rmihaylov/bert-base-squad-theseus-bg',
>>>     device=0,
>>>     revision=None)
>>>
>>> question = "С какво се проследява пандемията?"
>>> context = "Епидемията гасне, обяви при обявяването на данните тази сутрин Тодор Кантарджиев, член на Националния оперативен щаб. Той направи този извод на база на данните от математическите модели, с които се проследява развитието на заразата. Те показват, че т. нар. ефективно репродуктивно число е вече в границите 0.6-1. Тоест, 10 души заразяват 8, те на свой ред 6 и така нататък. "

>>> output = model(**{'question': question, 'context': context})
>>> print(output)

{'score': 0.85157310962677, 'start': 162, 'end': 186, 'answer': ' математическите модели,'}
```