transformers pytorch bert named entity recognition zh dataset:CMeEE license:apache-2.0 endpoints_compatible region:us
---
datasets:
- CMeEE
language:
- zh
license: apache-2.0
metrics:
- micro f1
tags:
- named entity recognition
---

# Global Pointer实体抽取模型

## 模型介绍

+ 数据集：CMeEE中文医学文本命名实时识别

+ 模型方法：[Efficient GlobalPointer：少点参数，多点效果](https://spaces.ac.cn/archives/8877)

## 使用方法

```commandline
pip install litie
```

```python
from pprint import pprint
from litie.pipelines import NerPipeline

pipline = NerPipeline("global-pointer", model_name_or_path="xusenlin/cmeee-global-pointer")
text = "可伴发血肿或脑梗死而出现局灶性神经体征，如肢体瘫痪及颅神经异常等。"
pprint(pipline(text))
```

更多模型的训练和推理详见 [lit-ie](https://github.com/xusenlinzy/lit-ie)
