--- language: "en" tags: - controlled generation - perturbation widget: - text: "[VERB+passive+past: break | PATIENT+partial: cup] ." - max_length: --- ​ # Polyjuice ​ ## Model description ​ This is a ported version of [Tailor](https://homes.cs.washington.edu/~wtshuang/static/papers/2021-arxiv-tailor.pdf), the general-purpose counterfactual generator. For more code release, please refer to [this github page](https://github.com/allenai/tailor). ​ #### How to use ​ ```python from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM ​ # TODO: change to the correct name model_path = "uw-hai/tailor_private" generator = pipeline("text2text-generation", model=AutoModelForSeq2SeqLM.from_pretrained(model_path), tokenizer=AutoTokenizer.from_pretrained(model_path), framework="pt", device=0) ​ prompt_text = "[VERB+active+past: comfort | AGENT+complete: the doctor | PATIENT+partial: athlete | LOCATIVE+partial: in] , ." generator(prompt_text, max_length=200) ```