raghakot/keras-text
A Keras-based library providing tokenizers, datasets, and pre-built neural network architectures for text classification.
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Keras-text is a text classification library that implements various state-of-the-art neural network models with a clean and extendable interface. It provides tokenizers for words, characters, and sentences, a dataset abstraction for managing training/test splits, and model factories for building classification architectures including YoonKimCNN and attention-based models. The library builds on top of Keras, TensorFlow, and Theano backends.
Frequently asked
- What is raghakot/keras-text?
- A Keras-based library providing tokenizers, datasets, and pre-built neural network architectures for text classification.
- Is keras-text open source?
- Yes — raghakot/keras-text is open source, released under the MIT license.
- What language is keras-text written in?
- raghakot/keras-text is primarily written in Python.
- How popular is keras-text?
- raghakot/keras-text has 421 stars on GitHub.
- Where can I find keras-text?
- raghakot/keras-text is on GitHub at https://github.com/raghakot/keras-text.