Active Learning for Text Classifcation in Python.
Active Learning allows you to efficiently label training data in a small-data scenario.
This library provides state-of-the-art active learning for text classification which allows to easily mix and match many classifiers and query strategies to build active learning experiments or applications.
- Provides unified interfaces for Active Learning so that you can easily use any classifier provided by sklearn.
- (Optionally) As an optional feature, you can also use pytorch classifiers, including transformers models.
- Multiple scientifically-proven strategies re-implemented: Query Strategies, Initialization Strategies
Small-text can be easily installed via pip:
pip install small-text
For a full installation include the transformers extra requirement:
pip install small-text[transformers]
Requires Python 3.7 or newer. For using the GPU, CUDA 10.1 or newer is required.
More information regarding the installation can be found in the
Read the latest documentation (currently work in progress) here.