Model Loading Imbalance
### System Info

- `transformers` version: 4.20.1
- Platform: Linux-5.4.0-81-generic-x86_64-with-glibc2.31
- Python version: 3.10.4
- Huggingface_hub version: 0.8.1
- PyTorch version (GPU?): 1.12.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: I guess I tried :)

### Who can help?

@patil-suraj @patrickvonplaten @LysandreJik 
This is a OPT related issue.

### Information

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

### Tasks

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

### Reproduction

```python
with init_empty_weights():
    model = OPTModel.from_pretrained("facebook/opt-6.7b", device_map="auto")
```

Model loading imbalance across the GPUs.

<img width="902" alt="image" src="https://user-images.githubusercontent.com/45140242/179495680-b1a4dae5-be85-4818-a969-8a58346be57d.png">


### Expected behavior

Model parameter numbers are balanced.
I think @sgugger is working on that as we speak<|||||>Yes, we will add support for more options to `device_map`, one of which is `"balanced"` after the next release. It's already available in Accelerate if you want to try it on.<|||||>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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.