---
language: zh
license: cc-by-sa-4.0
tags:
- word segmentation
datasets:
- ctb6 
- as
- cityu
- msra
- pku
- sxu
- cnc
pipeline_tag: token-classification
---

# Multi-criteria BERT base Chinese with Lattice for Word Segmentation

This is a variant of the pre-trained model [BERT](https://github.com/google-research/bert) model. 
The model was pre-trained on texts in the Chinese language and fine-tuned for word segmentation based on [bert-base-chinese](https://huggingface.co/bert-base-chinese).
This version of the model processes input texts with character-level with word-level incorporated with a lattice structure.

The scripts for the pre-training are available at [tchayintr/latte-ptm-ws](https://github.com/tchayintr/latte-ptm-ws).

The LATTE scripts are available at [tchayintr/latte-ws](https://github.com/tchayintr/latte-ws).

## Model architecture

The model architecture is described in this [paper](https://www.jstage.jst.go.jp/article/jnlp/30/2/30_456/_article/-char/ja).

## Training Data

The model is trained on multiple Chinese word segmented datasets, including ctb6, sighan2005 (as, cityu, msra, pku), sighan2008 (sxu), and cnc.
The datasets can be accessed from [here](https://github.com/hankcs/multi-criteria-cws/tree/master/data).

## Licenses

The pre-trained model is distributed under the terms of the [Creative Commons Attribution-ShareAlike 4.0](https://creativecommons.org/licenses/by-sa/4.0/).

## Acknowledgments

This model was trained with GPU servers provided by [Okumura-Funakoshi NLP Group](https://lr-www.pi.titech.ac.jp).