TextAttack

TextAttack is an open-source Python framework for adversarial attacks, data augmentation, and model training in Natural Language Processing (NLP). It provides tools to benchmark model robustness, generate adversarial examples, and create custom attack recipes. TextAttack supports integration with Hugging Face models and datasets, making it a versatile tool for research and experimentation in NLP security and performance.

Features of TextAttack:

• Supports a wide range of adversarial attack recipes for NLP models.
• Provides prebuilt and customizable pipelines for training and evaluation.
• Includes data augmentation techniques to improve model generalization.
• Compatible with Hugging Face Transformers and datasets.
• Offers CLI and Python APIs for flexible usage.
• Includes visualization tools for attack results and metrics.
• Supports benchmarking across multiple models and datasets.
• Open-source and actively maintained by the research community.

To verify the working of TextAttack in your environment:

$ sudo su
$ sudo apt update
$ cd /opt/TextAttack-0.3.10
$ source textattack-env/bin/activate
$ pip show textattack

Disclaimer: TextAttack is an open-source community project and is not affiliated with, endorsed by, or sponsored by OpenAI or any other company. The framework is provided "as is," without any warranty, express or implied. Users assume full responsibility for their usage, and the developers and contributors are not liable for any damages, losses, or consequences resulting from the use of TextAttack. Users should review and comply with licensing terms and applicable regulations when using TextAttack.