readme: ---
  language:
  - ru
  tags:
  - sentiment
  - text-classification
  datasets:
  - RuReviews
  ---
  
  # RuBERT for Sentiment Analysis of Product Reviews
  
  This is a [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model trained on [RuReviews](https://github.com/sismetanin/rureviews).
  
  ## Labels
      0: NEUTRAL
      1: POSITIVE
      2: NEGATIVE
  
  ## How to use
  ```python
  
  import torch
  from transformers import AutoModelForSequenceClassification
  from transformers import BertTokenizerFast
  
  tokenizer = BertTokenizerFast.from_pretrained('blanchefort/rubert-base-cased-sentiment-rurewiews')
  model = AutoModelForSequenceClassification.from_pretrained('blanchefort/rubert-base-cased-sentiment-rurewiews', return_dict=True)
  
  @torch.no_grad()
  def predict(text):
      inputs = tokenizer(text, max_length=512, padding=True, truncation=True, return_tensors='pt')
      outputs = model(**inputs)
      predicted = torch.nn.functional.softmax(outputs.logits, dim=1)
      predicted = torch.argmax(predicted, dim=1).numpy()
      return predicted
  ```
  
  
  ## Dataset used for model training
  
  **[RuReviews](https://github.com/sismetanin/rureviews)**
  
  > RuReviews: An Automatically Annotated Sentiment Analysis Dataset for Product Reviews in Russian.
  