readme: ## Usage:
  ```
  from sentence_transformers import models
  from sentence_transformers import SentenceTransformer
  
  word_embedding_model = models.Transformer('Cro-CoV-cseBERT')
  pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension(),
                                 pooling_mode_mean_tokens=True,
                                 pooling_mode_cls_token=False,
                                 pooling_mode_max_tokens=False)
  model = SentenceTransformer(modules=[word_embedding_model, pooling_model], device='')  ## device = 'gpu' or 'cpu'
  texts_emb = model.encode(texts)
  ```
  
  ## Datasets:
  https://github.com/InfoCoV/InfoCoV
  
  ## Paper:
  Please cite https://www.mdpi.com/2076-3417/11/21/10442