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--- |
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tags: salesken |
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license: apache-2.0 |
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inference: true |
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datasets: google_wellformed_query |
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widget: |
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- text: "what was the reason for everyone for leave the company" |
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--- |
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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. |
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['She is presenting a paper tomorrow','she is presenting a paper tomorrow','She present paper today'] |
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[[0.8917],[0.4270],[0.0134]] |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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tokenizer = AutoTokenizer.from_pretrained("salesken/query_wellformedness_score") |
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model = AutoModelForSequenceClassification.from_pretrained("salesken/query_wellformedness_score") |
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sentences = [' what was the reason for everyone to leave the company ', |
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' What was the reason behind everyone leaving the company ', |
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' why was everybody leaving the company ', |
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' what was the reason to everyone leave the company ', |
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' what be the reason for everyone to leave the company ', |
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' what was the reasons for everyone to leave the company ', |
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' what were the reasons for everyone to leave the company '] |
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features = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt") |
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model.eval() |
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with torch.no_grad(): |
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scores = model(**features).logits |
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print(scores) |
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``` |
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