| | --- |
| | language: |
| | - zh |
| | thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png |
| | tags: |
| | - pytorch |
| | - lm-head |
| | - bert |
| | - zh |
| | license: gpl-3.0 |
| | --- |
| | |
| | # CKIP BERT Base Chinese |
| |
|
| | This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word segmentation, part-of-speech tagging, named entity recognition). |
| |
|
| | 這個專案提供了繁體中文的 transformers 模型（包含 ALBERT、BERT、GPT2）及自然語言處理工具（包含斷詞、詞性標記、實體辨識）。 |
| |
|
| | ## Homepage |
| |
|
| | - https://github.com/ckiplab/ckip-transformers |
| |
|
| | ## Contributers |
| |
|
| | - [Mu Yang](https://muyang.pro) at [CKIP](https://ckip.iis.sinica.edu.tw) (Author & Maintainer) |
| |
|
| | ## Usage |
| |
|
| | Please use BertTokenizerFast as tokenizer instead of AutoTokenizer. |
| |
|
| | 請使用 BertTokenizerFast 而非 AutoTokenizer。 |
| |
|
| | ``` |
| | from transformers import ( |
| | BertTokenizerFast, |
| | AutoModel, |
| | ) |
| | |
| | tokenizer = BertTokenizerFast.from_pretrained('bert-base-chinese') |
| | model = AutoModel.from_pretrained('ckiplab/bert-base-chinese') |
| | ``` |
| |
|
| | For full usage and more information, please refer to https://github.com/ckiplab/ckip-transformers. |
| |
|
| | 有關完整使用方法及其他資訊，請參見 https://github.com/ckiplab/ckip-transformers 。 |
| |
|
