prompt2slip
This library is testing the ethics of language models by using natural adversarial texts.
This tool allows for short and simple code and validation with little effort.
Extensibility to be applied to any language model in any problem setting by inheriting from the base class.
Install
pip install prompt2slip
Usage
The simplest sample looks like this.
import prompt2slip
from transformers import GPT2Tokenizer, GPT2Model
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
model = GPT2Model.from_pretrained('gpt2')
base_text = ["This project respects pytorch developers."]
target_word = ["keras"]
target_ids = torch.Tensor(tokenizer.convert_tokens_to_ids(target_words))
attaker = CLMAttacker(model,tokenizer)
output = attacker.attack_by_text(texts,target_ids)
More realistic use cases are stored in examples.
What It Dose
"prompt2slip" provides the function to search for prompts which cause appearance of any specific word against a pre trained natural language generation model. Furthermore, with user customization, it can be applied to a wide range of tasks, including classification tasks.If you want to generate a hostile sample for a classification model, you can simply override the method to compute the adversarial loss function to generate a natural adversarial text.
The unique feature of this library is that it can generate test cases for verifying the danger of a pre-trained natural language model with a few lines of code.
References
More About This Project
License
Development
Install Package
Install poetry
poetry install
Test
Running tests with pytest.
poetry run pytest --cov .
1.2k Dec 18, 2022
125 Dec 20, 2022
2 Jan 17, 2022
1.2k Dec 21, 2022
2 May 17, 2022
2.9k Jan 2, 2023
65 Sep 13, 2022
21 Aug 12, 2022
431 Dec 19, 2022
3 May 25, 2022
4 Jul 1, 2022
66 Dec 26, 2022
20 Jan 9, 2023
1 Feb 7, 2022
148 Dec 26, 2022
76 Dec 14, 2022
124 Dec 29, 2022