---

license: apache-2.0
inference: false

datasets: google_wellformed_query
---

This model evaluates the wellformedness (non-fragment, grammatically correct)  score of a sentence. 
```
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)

```