update from v3.0.0 to v3.4.0 got an error
## Environment info
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- `transformers` version: v3.4.0
- Platform: redhat
- Python version: 3.8.3 64bit
- PyTorch version (GPU?): 1.5.1
- Tensorflow version (GPU?):
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no

### Who can help
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 albert, bert, GPT2, XLM: @LysandreJik 
 tokenizers: @mfuntowicz
 Trainer: @sgugger
 Speed and Memory Benchmarks: @patrickvonplaten
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 Translation: @sshleifer
 Summarization: @sshleifer
 TextGeneration: @TevenLeScao 
 examples/distillation: @VictorSanh
 nlp datasets: [different repo](https://github.com/huggingface/nlp)
 rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
 Text Generation: @patrickvonplaten @TevenLeScao
 blenderbot: @mariamabarham
 Bart: @sshleifer
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## Information

Model I am using (Bert, XLNet ...):
Bert
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

yesterday i used transformers v3.0.0 trained my model and save it use 
`torch.save(model.state_dict(), config.save_path)`, 
and today i update transformers to v3.4.0, when i use 
`torch.load` 
i got this error 
![image](https://user-images.githubusercontent.com/31238754/98341317-a2be1600-2049-11eb-9672-749896b9c2a4.png)
could anybody help me!!! thx

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

Hi! Yes, you should use the `from_pretrained` method to ensure compatibility within versions. Have you tried using that method instead? It should point to a directory containing your model file named as `pytorch_model.bin` and the configuration file of the model named as `config.json`.<|||||>> Hi! Yes, you should use the `from_pretrained` method to ensure compatibility within versions. Have you tried using that method instead? It should point to a directory containing your model file named as `pytorch_model.bin` and the configuration file of the model named as `config.json`.

Hi LysandreJik, I think you may misunderstand my problem. At the beginning of this project, I used `from_pretrained`, and when the training ended I use the `torch.save` saving the model to a .pth file(Under transformers v3.0.0). But under transformers v3.4.0, I init the model use `model = BertModel.from_pretrained(BertConfig.from_pretrained(configpath))`, then `model.load_state_dict(torch.load(modelpath)` and get this error. But under transformers v3.0.0, it's ok.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
