Kashgari

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Overview | Performance | Installation | Documentation | Contributing

🎉🎉🎉 We released the 2.0.0-alpha0 version with Seq2Seq Support. 🎉🎉🎉

Overview

Kashgari is a simple and powerful NLP Transfer learning framework, build a state-of-art model in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS), and text classification tasks.

  • Human-friendly. Kashgari’s code is straightforward, well documented and tested, which makes it very easy to understand and modify.

  • Powerful and simple. Kashgari allows you to apply state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS) and classification.

  • Built-in transfer learning. Kashgari built-in pre-trained BERT and Word2vec embedding models, which makes it very simple to transfer learning to train your model.

  • Fully scalable. Kashgari provides a simple, fast, and scalable environment for fast experimentation, train your models and experiment with new approaches using different embeddings and model structure.

  • Production Ready. Kashgari could export model with SavedModel format for tensorflow serving, you could directly deploy it on the cloud.

Our Goal

  • Academic users Easier experimentation to prove their hypothesis without coding from scratch.

  • NLP beginners Learn how to build an NLP project with production level code quality.

  • NLP developers Build a production level classification/labeling model within minutes.

Supporting the project

You can support the project by checking out our sponsor page. It takes only one click:

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Performance

Welcome to add performance report.

Task

Language

Dataset

Score

Named Entity Recognition

Chinese

People’s Daily Ner Corpus

93.66

Text Classification

Chinese

SMP2018ECDTCorpus

94.57

Neural machine translation

// TODO

Installation

The project is based on Python 3.6+, because it is 2019 and type hinting is cool.

Backend

pypi version

desc

TensorFlow 2.x

pip install 'kashgari>=2.0.0a0'

TF2 tf.keras - alpha version

TensorFlow 1.14+

pip install 'kashgari>=1.0.0,<2.0.0'

TF1.14+ tf.keras version

Keras

pip install 'kashgari<1.0.0'

keras version

Contributors ✨

Thanks goes to these wonderful people. And there are many ways to get involved. Start with the contributor guidelines and then check these open issues for specific tasks.