readme: ---
  tags: salesken
  license: apache-2.0
  inference: true
  
  datasets: google_wellformed_query
  
  widget:
   - text: "what was the reason for everyone for leave the company"
  ---
  
  This model evaluates the wellformedness (non-fragment, grammatically correct)  score of a sentence. Model is case-sensitive and penalises for incorrect case and grammar as well. 
  
  ['She is presenting a paper tomorrow','she is presenting a paper tomorrow','She present paper today']
  
  [[0.8917],[0.4270],[0.0134]]
  ```python
  from transformers import AutoTokenizer, AutoModelForSequenceClassification
  tokenizer = AutoTokenizer.from_pretrained("salesken/query_wellformedness_score")
  model = AutoModelForSequenceClassification.from_pretrained("salesken/query_wellformedness_score")
  sentences = [' what was the reason for everyone to leave the company ', 
                 ' What was the reason behind everyone leaving the company ', 
                 ' why was everybody leaving the company ', 
                 ' what was the reason to everyone leave the company ',
                 ' what be the reason for everyone to leave the company ', 
                 ' what was the reasons for everyone to leave the company ', 
                 ' what were the reasons for everyone to leave the company ']
  
  features = tokenizer(sentences,  padding=True, truncation=True, return_tensors="pt")
  model.eval()
  with torch.no_grad():
      scores = model(**features).logits
  print(scores)
  
  ```
  
  
  