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@@ -14,6 +14,23 @@ This model evaluates the wellformedness (non-fragment, grammatically correct) s
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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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  ['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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+ 1. Dogs are mammals.
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+ 2. she loves to read books on history.
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+ 3. When the rain in Spain.
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+ 4. Eating apples are healthy for you.
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+ 5. The Eiffel Tower is in Paris.
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+
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+ Among these sentences:
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+ Sentences 1 and 5 are well-formed and have correct grammar and case.
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+ Sentence 2 starts with a lowercase letter.
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+ Sentence 3 is a fragment and is not well-formed.
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+ Sentence 4 has a subject-verb agreement error.
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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")