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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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GED_TOKENIZER = AutoTokenizer.from_pretrained("zuu/grammar-error-correcter") |
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GED_MODEL = AutoModelForSeq2SeqLM.from_pretrained("zuu/grammar-error-correcter") |
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# Incorrect text |
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incorrect_text = 'young children should avoid exposure to contageous disease' |
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# Tokenize text |
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tokens= GED_TOKENIZER( |
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[incorrect_text], |
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padding=True, |
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return_tensors='pt' |
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) |
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corrections = GED_MODEL.generate(**tokens) |
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corrections = GED_TOKENIZER.batch_decode( |
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corrections, |
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skip_special_tokens=True |
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) |
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``` |