| """.. _models: | |
| Models | |
| ========= | |
| TextAttack can attack any model that takes a list of strings as input and outputs a list of predictions. This is the idea behind *model wrappers*: to help your model conform to this API, we've provided the ``textattack.models.wrappers.ModelWrapper`` abstract class. | |
| We've also provided implementations of model wrappers for common patterns in some popular machine learning frameworks: | |
| Models User-specified | |
| -------------------------- | |
| TextAttack allows users to provide their own models for testing. Models can be loaded in three ways: | |
| 1. ``--model`` for pre-trained models and models trained with TextAttack | |
| 2. ``--model-from-huggingface`` which will attempt to load any model from the ``HuggingFace model hub <https://huggingface.co/models>`` | |
| 3. ``--model-from-file`` which will dynamically load a Python file and look for the ``model`` variable | |
| Models Pre-trained | |
| -------------------------- | |
| TextAttack also provides lots of pre-trained models for common tasks. Testing different attacks on the same model ensures attack comparisons are fair. | |
| Any of these models can be provided to ``textattack attack`` via ``--model``, for example, ``--model bert-base-uncased-mr``. For a full list of pre-trained models, see the `pre-trained models README <https://github.com/QData/TextAttack/tree/master/textattack/models>`_. | |
| Model Wrappers | |
| -------------------------- | |
| TextAttack can attack any model that takes a list of strings as input and outputs a list of predictions. This is the idea behind *model wrappers*: to help your model conform to this API, we've provided the ``textattack.models.wrappers.ModelWrapper`` abstract class. | |
| We've also provided implementations of model wrappers for common patterns in some popular machine learning frameworks: including pytorch / sklearn / tensorflow. | |
| """ | |
| from . import helpers | |
| from . import tokenizers | |
| from . import wrappers | |