# Whole Word Masking Pre-training

NEZHA is a Chinese pre-trained language model based on the Transformer architecture, optimized for Chinese text understanding tasks using the whole word masking strategy

A Chinese pre-trained BERT model employing whole word masking strategy, aimed at accelerating Chinese natural language processing research.

This is a retrained three-layer RoBERTa-wwm-ext-large model, a Chinese pre-trained BERT model employing whole word masking strategy, aimed at accelerating the development of Chinese natural language processing.

This is a Chinese pre-trained BERT model employing whole word masking technology, developed by the HIT-iFLYTEK Joint Lab to accelerate advancements in Chinese natural language processing.

CAMeLBERT-DA is a BERT model pre-trained on Dialectal Arabic (DA), part of the CAMeLBERT series, specializing in Arabic NLP tasks.