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Generating adversarial examples for NLP models. TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP.
Features
- Understand NLP models better by running different adversarial attacks on them and examining the output
- Research and develop different NLP adversarial attacks using the TextAttack framework and library of components
- Augment your dataset to increase model generalization and robustness downstream
- Train NLP models using just a single command (all downloads included!)
- Documentation available
- You should be running Python 3.6+ to use this package
- Pre-trained Models for testing attacks and evaluating constraints
- Visualization options like Weights & Biases and Visdom
- AttackedText, a utility class for strings that includes tools for tokenizing and editing text
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow TextAttack
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