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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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class GrammarCorrector:
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def __init__(self, model_name="vennify/t5-base-grammar-correction"):
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self.tokenizer = AutoTokenizer.from_pretrained(model_name)
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self.model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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def correct(self, text):
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input_text = "gec: " + text
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input_ids = self.tokenizer.encode(input_text, return_tensors="pt")
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outputs = self.model.generate(input_ids, max_length=128, num_beams=5, early_stopping=True)
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corrected_text = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
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return corrected_text
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