Text2Text Generation
Safetensors
Azerbaijani
t5
spell
correction
azerbaijani
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@@ -91,6 +91,26 @@ These substitutions represent phonetic similarities and common mistakes made by
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  To use the model for spell correction:
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  ## License
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  To use the model for spell correction:
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+ ```python
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+ import torch
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+ from transformers import MT5ForConditionalGeneration, MT5Tokenizer
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+
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+ # Load the tokenizer and model
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+ tokenizer = MT5Tokenizer.from_pretrained('LocalDoc/azerbaijani_spell_corrector')
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+ model = MT5ForConditionalGeneration.from_pretrained('LocalDoc/azerbaijani_spell_corrector')
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+
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+ # Function to correct sentences
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+ def correct_sentence(sentence):
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+ input_text = "correct: " + sentence
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+ input_ids = tokenizer.encode(input_text, return_tensors='pt', max_length=128, truncation=True)
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+ outputs = model.generate(input_ids=input_ids, max_length=128, num_beams=5, early_stopping=True)
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+ corrected_sentence = tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ return corrected_sentence
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+
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+ # Example usage
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+ incorrect_sentence = "Pul dogru adamlarda deyil"
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+ print(correct_sentence(incorrect_sentence))
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+ ```
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  ## License
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