|
--- |
|
language: |
|
- zh |
|
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png |
|
tags: |
|
- pytorch |
|
- question-answering |
|
- 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-qa') |
|
``` |
|
|
|
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 。 |
|
|
