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--- |
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language: en |
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--- |
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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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``` |
