ckiplab/ckip-transformers
A Python library providing Traditional Chinese transformer models (ALBERT, BERT, GPT2) and NLP tools for word segmentation, POS tagging, and named entity recognition.
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This project provides pre-trained transformer models for Traditional Chinese language processing, including tokenization and sequence labeling tasks. It offers easy-to-use pipelines for word segmentation, part-of-speech tagging, and named entity recognition using ALBERT, BERT, and GPT2 architectures optimized for Chinese text. The library wraps these transformer models in a user-friendly interface for common NLP tasks.
Frequently asked
- What is ckiplab/ckip-transformers?
- A Python library providing Traditional Chinese transformer models (ALBERT, BERT, GPT2) and NLP tools for word segmentation, POS tagging, and named entity recognition.
- Is ckip-transformers open source?
- Yes — ckiplab/ckip-transformers is open source, released under the GPL-3.0 license.
- What language is ckip-transformers written in?
- ckiplab/ckip-transformers is primarily written in Python.
- How popular is ckip-transformers?
- ckiplab/ckip-transformers has 768 stars on GitHub.
- Where can I find ckip-transformers?
- ckiplab/ckip-transformers is on GitHub at https://github.com/ckiplab/ckip-transformers.