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Update README.md

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@@ -24,4 +24,33 @@ If a question is not directed, we would change the actions we perform on a RAG p
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  (Class 0 is Generic; Class 1 is Directed)
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- The accuracy on the training dataset is around 87.5%
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  (Class 0 is Generic; Class 1 is Directed)
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+ The accuracy on the training dataset is around 87.5%
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+
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+ ```python
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+ from transformers import BertForSequenceClassification, BertTokenizerFast
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+ import torch
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+
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+ # Load the model and tokenizer
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+ model = BertForSequenceClassification.from_pretrained("cnmoro/bert-tiny-question-classifier")
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+ tokenizer = BertTokenizerFast.from_pretrained("cnmoro/bert-tiny-question-classifier")
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+
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+ def is_question_generic(question):
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+ # Tokenize the sentence and convert to PyTorch tensors
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+ inputs = tokenizer(
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+ question.lower(),
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+ truncation=True,
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+ padding=True,
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+ return_tensors="pt",
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+ max_length=512
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+ )
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+
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+ # Get the model's predictions
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+ with torch.no_grad():
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+ outputs = model(**inputs)
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+
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+ # Extract the prediction
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+ predictions = outputs.logits
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+ predicted_class = torch.argmax(predictions).item()
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+
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+ return int(predicted_class) == 0
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+ ```