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This model receives scrambled or incoherent sentences as input and returns a meaningful sentence using the same words in the input . A form of grammar correction if you may . It was trained on a dataset of permutated sentences derived from wikipedia pages as input with the correct arrangement of words as labels . It is an encoder-decoder model that uses BERT's weight in both it's encoder and decoder .
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("damilojohn/Bert2BertForTextDescrambling") model = AutoModelForSeq2SeqLM.from_pretrained("damilojohn/Bert2BertForTextDescrambling")