README.md

metadata

language: en
tags:
  - controlled generation
  - perturbation
widget:
  - text: >-
      [VERB+passive+past: break | PATIENT+partial: cup] <extra_id_0>
      <extra_id_1> <extra_id_2> .
  - max_length: null

​

Polyjuice

​

Model description

​ This is a ported version of Tailor, the general-purpose counterfactual generator. For more code release, please refer to this github page. ​

How to use

​

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] <extra_id_0> , <extra_id_1> <extra_id_2> <extra_id_3> ."
generator(prompt_text, max_length=200)