| ## bert-from-clip-chinese pretrained model | |
| 该预训练权重是从BertCLIP预训练模型中单独取出来的Bert的权重，BertCLIP是中文版本的CLIP预训练模型，基于LiT-tuning（Locked-image Text tuning）的策略， | |
| 使用140万中文图文对数据进行多模态对比学习预训练。 | |
| Github: [CLIP-Chinese](https://github.com/yangjianxin1/CLIP-Chinese) | |
| Bolg: [CLIP-Chinese：中文多模态对比学习CLIP预训练模型](https://mp.weixin.qq.com/s/6gQX91M-Lt7eiMimhYRJEw) | |
| ## Usage | |
| 可以直接使用Huggingface的BertModel直接加载该预训练权重，进行下游的任务。 | |
| ```python | |
| from transformers import BertTokenizer, BertModel | |
| model_name_or_path = 'YeungNLP/bert-from-clip-chinese-1M' | |
| tokenizer = BertTokenizer.from_pretrained(model_name_or_path) | |
| model = BertModel.from_pretrained(model_name_or_path) | |
| ``` |