Avoiding the time consuming for downloading the pre-trained models
# 📚 Migration
Very great project! I can successfully run the code:

```
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("bert-base-chinese")
model_Bert = AutoModel.from_pretrained("bert-base-chinese")
```

But, every time I run my code, the downloading processing are repeated, which is time consuming. So I wonder how to load the pre-trained models from my local directory instead of downloading the pre-trained models everytime?
Hi! It should work (examples for Linux systems)
```python
# Save model to directory:
model.save_pretrained("./my_model_directory/") 

# Load model from directory:
model = AutoModel.from_pretrained("./my_model_directory/")

####################### OR ###########################

# Cache model to directory:
model = AutoModel.from_pretrained("bert-base-chinese", cache_dir="./my_model_directory/")
```<|||||>Thanks! It is useful for me. One more question: I found that the files saved in "./my_model_directory/" contain config.json, pytorch_model.bin, and other .json files, but do not contain 'vocab.txt', is it reasonable?<|||||>I think `vocab.txt` is only needed for the tokenizer. The tokenizer can also be saved in the same directory.<|||||>When you do 
```
tokenizer = AutoTokenizer.from_pretrained("bert-base-chinese")
model_Bert = AutoModel.from_pretrained("bert-base-chinese")
```

this should be caching the files in your local cache, it shouldn't redownload the files every time. You shouldn't need to specify a local folder in which to save them.

How are you identifying that the files are redownloaded every time?<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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