metadata
language:
- zh
license: apache-2.0
tags:
- classification
inference: false
IDEA-CCNL/Erlangshen-TCBert-110M-Sentence-Embedding-Chinese
- Github: Fengshenbang-LM
- Docs: Fengshenbang-Docs
简介 Brief Introduction
110M参数的Topic Classification BERT (TCBert)。
The TCBert with 110M parameters is pre-trained for, not limited to, Chinese topic classification tasks.
模型分类 Model Taxonomy
需求 Demand | 任务 Task | 系列 Series | 模型 Model | 参数 Parameter | 额外 Extra |
---|---|---|---|---|---|
通用 General | 句子表征 | 二郎神 Erlangshen | TCBert | 110M | Chinese |
模型信息 Model Information
为了提高模型在话题分类上句子表征效果,我们收集了大量话题分类数据进行基于prompts的对比学习预训练。
To improve the model performance on the topic classification task, we collected numerous topic classification datasets for contrastive pre-training based on general prompts.
下游效果 Performance
Stay tuned.
使用 Usage
from transformers import BertForMaskedLM, BertTokenizer
import torch
tokenizer=BertTokenizer.from_pretrained("IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese")
model=BertForMaskedLM.from_pretrained('IDEA-CCNL/Erlangshen-TCBert-110M-Classification-Chinese')
Stay tuned for more details.
如果您在您的工作中使用了我们的模型,可以引用我们的网站:
You can also cite our website:
@misc{Fengshenbang-LM,
title={Fengshenbang-LM},
author={IDEA-CCNL},
year={2021},
howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
}