Create README.md
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README.md
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---
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inference: false
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language:
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- bg
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license: mit
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datasets:
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- oscar
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- chitanka
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- wikipedia
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tags:
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- torch
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---
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# BERT BASE (cased) finetuned on Bulgarian squad data
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Pretrained model on Bulgarian language using a masked language modeling (MLM) objective. It was introduced in
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[this paper](https://arxiv.org/abs/1810.04805) and first released in
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[this repository](https://github.com/google-research/bert). This model is cased: it does make a difference
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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/).
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It was finetuned on private squad Bulgarian data.
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Then, it was compressed via [progressive module replacing](https://arxiv.org/abs/2002.02925).
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### How to use
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Here is how to use this model in PyTorch:
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```python
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>>> from transformers import pipeline
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>>>
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>>> model = pipeline(
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>>> 'question-answering',
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>>> model='rmihaylov/bert-base-squad-theseus-bg',
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>>> tokenizer='rmihaylov/bert-base-squad-theseus-bg',
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>>> device=0,
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>>> revision=None)
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>>>
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>>> question = "С какво се проследява пандемията?"
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>>> 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. "
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>>> output = model(**{'question': question, 'context': context})
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>>> print(output)
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{'score': 0.85157310962677, 'start': 162, 'end': 186, 'answer': ' математическите модели,'}
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```
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