readme: ---
  language: en
  ---
  
  # CTRL44 Simplification model
  
  This is a pretrained version of the controllable simplification model presented in the NAACL 2022 paper "Controllable Sentence Simplification via Operation Classification". It was trained on the IRSD simplification dataset.
  
  A control token is expected at the start of input sequences to dictate which simplification operation should be performed. This can either be done manually or with an operation classifier like [this one](https://huggingface.co/liamcripwell/ctrl44-clf).
  
  Possible control tokens are: "\<ident\>", "\<para\>", "\<ssplit\>", and "\<dsplit\>".
  
  ## How to use
  
  Here is how to use this model in PyTorch:
  
  ```python
  from transformers import BartForConditionalGeneration, AutoTokenizer
  
  model = BartForConditionalGeneration.from_pretrained("liamcripwell/ctrl44-simp")
  tokenizer = AutoTokenizer.from_pretrained("liamcripwell/ctrl44-simp")
  
  text = "<para> Barack Hussein Obama II is an American politician who served as the 44th president of the United States from 2009 to 2017."
  inputs = tokenizer(text, return_tensors="pt")
  outputs = model.generate(**inputs, num_beams=10, max_length=128)
  ```