报错信息
OSError: We couldn’t connect to ‘https://huggingface.co’ to load this file, couldn’t find it in the cached files and it looks like jinaai/jina-bert-implementation is not the path to a directory containing a file named configuration_bert.py.
报错信息简述是连不上huggingface网址，也找不到缓存文件，缺失jinaai/jina-bert-implementation路径的configuration_bert.py文件。
网上也有好多解决的方法，对我来说感觉都太复杂了。
现在提供我的解决思路，非常简单，希望对你有帮助。
解决方法
在使用jinaai/jina-embeddings-v2-base-zh向量模型时，发现会报错信息如上。
此时我们还需要下载这个模型jinaai/jina-bert-implementation。
Huggling Face 下载
# Load model directly
from transformers import AutoTokenizer, AutoModel
model = "jinaai/jina-embeddings-v2-base-zh"
tokenizer = AutoTokenizer.from_pretrained(model , cache_dir="./", trust_remote_code=True)
model = AutoModel.from_pretrained(model , cache_dir="./", trust_remote_code=True)
网不好的使用国内的魔塔下载
jina-bert-implementation模型下载
jina-embeddings-v2-base-zh模型下载
建议手动下载，因为里面有很多而外的文件，速度比较慢。
以上两种方式下载完成后，最后整理一下文件，两个模型最小包含文件如下：
我存放的目录为 /home/jinaai/
/home/jinaai/
├── jina-bert-implementation
│ ├── configuration_bert.py
│ └── modeling_bert.py
└── jina-embeddings-v2-base-zh
├── config.json
├── merges.txt
├── model.safetensors
├── special_tokens_map.json
├── tokenizer_config.json
├── tokenizer.json
└── vocab.json
修改jina-embeddings-v2-base-zh模型config.json配置文件，将红色框中的路径换成jina-bert-implementation模型实际的路径即可。
测试是否成功
from numpy.linalg import norm
import torch
from transformers import AutoModel
from numpy.linalg import norm
if __name__ == "__main__":
path = "/home/jinaai/jina-embeddings-v2-base-zh"
cos_sim = lambda a,b: (a @ b.T) / (norm(a)*norm(b))
model = AutoModel.from_pretrained(path, trust_remote_code=True, torch_dtype=torch.bfloat16)
embeddings = model.encode(['How is the weather today?', '今天天气怎么样?'])
print(cos_sim(embeddings[0], embeddings[1]))
# 打印结果: 0.7868529
完美解决 OSError: We couldn’t connect to ‘https://huggingface.co’ to load this file, couldn’t find it in the cached files and it looks like jinaai/jina-bert-implementation is not the path to a directory containing a file named configuration_bert.py.这个报错，祝你好运~
