# bert-base-chinese-ner

**Repository Path**: tansohu/bert-base-chinese-ner

## Basic Information

- **Project Name**: bert-base-chinese-ner
- **Description**: BERT-Base-Chinese-NER 是一个基于BERT架构的中文命名实体识别模型。该模型在大规模的中文语料库上进行了预训练，能够有效地识别文本中的实体名称，如人名、地名、组织机构等。BERT-Base-Chinese-NER 在命名实体识别任务中表现出色，为中文文本处理和信息抽取任务提供了有力的支持。
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2026-03-26
- **Last Updated**: 2026-03-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

---
language:
  - zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
  - pytorch
  - token-classification
  - 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-ner')
```

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 。