Fill-Mask
Transformers
PyTorch
Chinese
bert
Inference Endpoints
File size: 1,629 Bytes
9f99fbe
c7d8981
26c56bf
 
9f99fbe
 
4b129f0
2997e5c
4b129f0
cf71bac
4b129f0
 
b116f07
2944ead
4b129f0
 
 
 
 
 
 
4f7218f
 
 
4b129f0
 
f421fc8
4b129f0
 
4f7218f
 
 
 
 
4b129f0
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
---
language: zh
tags:
- bert
license: apache-2.0
---
## Chinese DKPLM (Decomposable Knowledge-enhanced Pre-trained Language Model) for the medical domain
For Chinese natural language processing in specific domains, we provide **Chinese DKPLM (Decomposable Knowledge-enhanced Pre-trained Language Model)** for the medical domain named **pai-dkplm-bert-zh**.

**[DKPLM: Decomposable Knowledge-enhanced Pre-trained Language Model for Natural Language Understanding](https://arxiv.org/abs/2112.01047)**  
Taolin Zhang, Chengyu Wang, Nan Hu, Minghui Qiu, Chengguang Tang, Xiaofeng He, Jun Huang

This repository is developed based on the EasyNLP framework: [https://github.com/alibaba/EasyNLP](https://github.com/alibaba/EasyNLP ) developed by the Alibaba PAI team.

## Citation
If you find the resource is useful, please cite the following papers in your work.

- For the EasyNLP framework:
```
@article{easynlp, 
title = {EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing},   			publisher = {arXiv}, 
  author = {Wang, Chengyu and Qiu, Minghui and Zhang, Taolin and Liu, Tingting and Li, Lei and Wang, Jianing and Wang, Ming and Huang, Jun and Lin, Wei}, 
  url = {https://arxiv.org/abs/2205.00258}, 
  year = {2022} 
} 
```
- For DKPLM:
```
@article{dkplm, 
  title = {DKPLM: Decomposable Knowledge-enhanced Pre-trained Language Model for Natural Language Understanding}, 
  author = {Zhang, Taolin and Wang, Chengyu and Hu, Nan and Qiu, Minghui and Tang, Chengguang and He, Xiaofeng and Huang, Jun}, 
  url = {https://arxiv.org/abs/2112.01047},   			
  publisher = {arXiv}, 
  year = {2021} 
} 
```