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---
tags:
- salesken
license: apache-2.0
inference: true
datasets: google_wellformed_query
widget:
text: "she present paper today"
---
model_card:
model_name: Salesken's Query Wellformedness Score Model
description: Evaluate the well-formedness of sentences by checking grammatical correctness and completeness. Sensitive to case and penalizes sentences for incorrect grammar and case.
features:
- Wellformedness Score: Provides a score indicating grammatical correctness and completeness.
- Case Sensitivity: Recognizes and penalizes incorrect casing in sentences.
- Broad Applicability: Can be used on a wide range of sentences.
evaluation_results:
input:
- She is presenting a paper tomorrow
- she is presenting a paper tomorrow
- She present paper today
scores:
- 0.8917
- 0.4270
- 0.0134
1. Dogs are mammals.
2. she loves to read books on history.
3. When the rain in Spain.
4. Eating apples are healthy for you.
5. The Eiffel Tower is in Paris.
Among these sentences:
Sentences 1 and 5 are well-formed and have correct grammar and case.
Sentence 2 starts with a lowercase letter.
Sentence 3 is a fragment and is not well-formed.
Sentence 4 has a subject-verb agreement error.
example_usage:
library: HuggingFace transformers
```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',
# ... other sentences
]
features = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt")
model.eval()
with torch.no_grad():
scores = model(**features).logits
print(scores)
```
intended_use_cases:
- Content Creation: Validate the well-formedness of written content.
- Educational Platforms: Students check the grammaticality of sentences.
- Chatbots & Virtual Assistants: Validate user queries or generate well-formed responses.
limitations:
- Model might have occasional inaccuracies or biases.
- Long sentences might be truncated, affecting score.
contact: contact@salesken.ai
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