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# CTRL44 Simplification model
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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.
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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).
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Possible control tokens are: "\<ident\>", "\<para\>", "\<ssplit\>", and "\<dsplit\>".
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## How to use
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Here is how to use this model in PyTorch:
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```python
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from transformers import BartForConditionalGeneration, AutoTokenizer
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model = BartForConditionalGeneration.from_pretrained("liamcripwell/ctrl44-simp")
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tokenizer = AutoTokenizer.from_pretrained("liamcripwell/ctrl44-simp")
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text = "<para> Barack Hussein Obama II is an American politician who served as the 44th president of the United States from 2009 to 2017."
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model.generate(**inputs, num_beams=10, max_length=128)
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```
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