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Kashgari
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About Kashgari
Kashgari is an open source NLP (Natural Language Processing) framework designed to help developers build state-of-the-art deep learning models for text classification and sequence labeling tasks. With Kashgari, users can quickly and easily create models that can leverage the power of deep learning to solve complex NLP problems. Kashgari’s intuitive interface makes it easy to develop complex neural network models, and the library’s powerful set of APIs allows for a wide range of customizations and experimentation. Kashgari also provides a range of pre-trained models that can be used for a variety of tasks, such as sentiment analysis, intent classification, and text summarization. Its comprehensive documentation and comprehensive set of tutorials make it easy for developers to get started. With Kashgari, developers can take their NLP applications to the next level with powerful, easy-to-use deep learning models. Kashgari is suitable for developers who want to build state-of-the-art deep learning models for text classification and sequence labeling tasks. It provides a range of pre-trained models that can be used for various tasks, including sentiment analysis, intent classification, and text summarization.
GitHub, Inc.
San Francisco, California, US · Founded 2008
- Founders
- Tom Preston-Werner, Chris Wanstrath, PJ Hyett, Scott Chacon
- Founded
- 2008
- Headquarters
- San Francisco, California, US
- Legal status
- Subsidiary of Microsoft (NASDAQ: MSFT)
Key features
- Automate text classification for sentiment analysis
- Generate text summarization for long documents
- Detect intent from customer feedback
- Intuitive interface for developing complex neural network models
- Powerful set of APIs for customizations and experimentation
- Range of pre-trained models for various tasks
Use cases
- Automate sentiment analysis for customer reviews
- Generate text summaries for long documents, such as research papers or articles
- Detect intent from customer feedback to improve customer service
Pros
- Open-source NLP transfer learning framework built on TensorFlow 2.x and Keras
- Supports state-of-the-art models for named entity recognition (NER), part-of-speech tagging (PoS), and text classification
- Includes built-in pre-trained embeddings such as BERT, Word2Vec, and GPT-2 for quick model development
- Provides production-ready model export in SavedModel format for TensorFlow Serving deployment
- Offers human-friendly, well-documented, and tested code for ease of understanding and modification
Cons
- Limited official support beyond community resources and documentation
- Requires familiarity with Python and TensorFlow/Keras for advanced customization
- Dependency on specific TensorFlow versions may complicate integration in some environments
Frequently asked questions about Kashgari
What is Kashgari and what does it do?
Kashgari is an open-source NLP transfer learning framework built on top of TensorFlow and Keras, designed for text labeling and text classification tasks such as named entity recognition, part-of-speech tagging, and sentiment analysis.
Who is Kashgari suitable for?
Kashgari is suitable for academic users seeking easier experimentation, NLP beginners learning to build projects with production-level code, and NLP developers aiming to create production-ready models quickly.
How do I install Kashgari?
Kashgari requires Python 3.6+ and can be installed via pip with versions tailored for TensorFlow 1.x or 2.x, such as 'pip install kashgari>=2.0.2' for TensorFlow 2.2+ or 'pip install kashgari>=1.0.0,
Does Kashgari support pre-trained models?
Yes, Kashgari includes built-in pre-trained models like BERT and Word2Vec embeddings, enabling users to leverage transfer learning for tasks such as named entity recognition and text classification.
Can models built with Kashgari be deployed in production?
Yes, Kashgari supports exporting models in the SavedModel format, which can be directly deployed using TensorFlow Serving or other cloud-based serving solutions.
Where can I find tutorials to get started with Kashgari?
Kashgari provides a set of quick tutorials covering text classification, text labeling, and sequence-to-sequence tasks, available in the project's documentation and examples.
