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