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| language: en |
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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 |
| from transformers import BartForConditionalGeneration, AutoTokenizer |
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| model = BartForConditionalGeneration.from_pretrained("liamcripwell/ctrl44-simp") |
| 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." |
| inputs = tokenizer(text, return_tensors="pt") |
| outputs = model.generate(**inputs, num_beams=10, max_length=128) |
| ``` |
