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
                                      )