| ```python | |
| 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 | |
| ) | |
| ``` |