error when load model
### System Info

2023-07-19 13:47:33.834732: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT


### Who can help?

_No response_

### Information

- [x] The official example scripts
- [ ] My own modified scripts

### Tasks

- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

model = BertForSequenceClassification.from_pretrained('bert-base-uncased',
                                                      num_labels = 2)
model.to(device)
model.load_state_dict(torch.load("my_model.pt", map_location = torch.device("cpu")))

### Expected behavior

When running the code, it shows run time error: _IncompatibleKeys(missing_keys=[], unexpected_keys=['bert.embeddings.position_ids']). The error does not occur yesterday, but appear now. 
You will need to drop that key from your state dict, or use the `save_pretrained` and `from_pretrained` method of the library.<|||||>I'm having the same issue, except my model is a custom model that includes a transformer model as a part of it so I need to use `torch.load_state_dict` to load the model.

Here's some code to reproduce the issue:

```python
import torch.nn as nn
from transformers import XLMRobertaConfig, XLMRobertaModel


class MyCustomModel(nn.Module):
    def __init__(self):
        super().__init__()
        self.roberta = XLMRobertaModel(
            XLMRobertaConfig.from_pretrained("Unbabel/xlm-roberta-comet-small")
        )
        self.my_thing = nn.Linear(384, 1)  # let's pretend this is way more complicated


def main():
    model = MyCustomModel()

    print(sorted(list(model.state_dict().keys()))[:10])


if __name__ == "__main__":
    main()
```

When running the script with transformers==4.30.0 (which is what I used for training the model) I get the following output:

```
['my_thing.bias', 'my_thing.weight', 'roberta.embeddings.LayerNorm.bias', 'roberta.embeddings.LayerNorm.weight', 'roberta.embeddings.position_embeddings.weight', 'roberta.embeddings.position_ids', 'roberta.embeddings.token_type_embeddings.weight', 'roberta.embeddings.word_embeddings.weight', 'roberta.encoder.layer.0.attention.output.LayerNorm.bias', 'roberta.encoder.layer.0.attention.output.LayerNorm.weight']
```

Note the presence of `roberta.embeddings.position_ids`.

Now when I try to load the model using transformers==4.31.0, it gives me a key error, because the position IDs key seems to have been removed in the new version. Running the same code gives:

```
['my_thing.bias', 'my_thing.weight', 'roberta.embeddings.LayerNorm.bias', 'roberta.embeddings.LayerNorm.weight', 'roberta.embeddings.position_embeddings.weight', 'roberta.embeddings.token_type_embeddings.weight', 'roberta.embeddings.word_embeddings.weight', 'roberta.encoder.layer.0.attention.output.LayerNorm.bias', 'roberta.encoder.layer.0.attention.output.LayerNorm.weight', 'roberta.encoder.layer.0.attention.output.dense.bias']
```

The position IDs key is not there anymore.

Shouldn't this at least be documented as a breaking change in the release notes?<|||||>Same issue here<|||||>You should use `save_pretrained` and `from_pretained` to save/load your models. There is no breaking changes with those methods, we do not guarantee the same if you choose to save/load your model on your own across different versions of Transformers.