pytorch albert token-classification zh transformers license:gpl-3.0
.gitattributes README.md config.json pytorch_model.bin special_tokens_map.json tokenizer_config.json vocab.txt
---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- albert
- zh
license: gpl-3.0
datasets:
metrics:
---

# CKIP ALBERT 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/albert-base-chinese-pos')
```

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 。
