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README.md
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---
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license: mit
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---
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---
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license: mit
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language:
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- ru
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pipeline_tag: text-classification
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widget:
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- text: 'что такое QR-код'
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- text: 'когда деньги придут за мной'
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- text: 'почему девушки мне не дают'
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---
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# Den4ikAI/ruBert-tiny-questions-classifier
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Модель классифицирует вопрос на два класса:
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1. Точный вопрос (exact_question) - вопрос требующий четкого, фактологичного ответа.
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2. Неточный вопрос (innacurate_question) - вопрос допускающий рассуждения, философские вопросы.
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# Использование
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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class RuBertQuestionClassifier:
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def __init__(self):
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self.device = torch.device("cpu")
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self.tokenizer = AutoTokenizer.from_pretrained("Den4ikAI/ruBert-tiny-questions-classifier")
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self.model = AutoModelForSequenceClassification.from_pretrained("Den4ikAI/ruBert-tiny-questions-classifier").to(
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self.device).eval()
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self.classes = ['exact_question', 'inaccurate_question']
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def get_question_type(self, text):
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text = text.lower().replace(',', '').replace('?', '')
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inputs = self.tokenizer(text, max_length=512, add_special_tokens=False, truncation=True,
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return_tensors='pt').to(self.device)
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with torch.no_grad():
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logits = self.model(**inputs).logits
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probas = list(torch.sigmoid(logits)[0].cpu().detach().numpy())
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out = self.classes[probas.index(max(probas))]
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self.logger.debug('Mode: {}'.format(out))
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return out
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classifier = RuBertQuestionClassifier()
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print(classifier.get_question_type('когда я найду своего принца'))
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print(classifier.get_question_type('что такое цианид'))
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```
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# Citation
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```
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@MISC{Den4ikAI/ruBert-tiny-questions-classifier,
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author = {Denis Petrov},
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title = {Russian question type classifier model},
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url = {https://huggingface.co/Den4ikAI/ruBert-tiny-questions-classifier},
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year = 2023
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}
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```
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