CUDA out of memory even for GPT-NEO-125M
## Environment info
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- `transformers` version: 4.11.0.dev0
- Platform: Linux-4.15.0-156-generic-x86_64-with-glibc2.17
- Python version: 3.8.11
- PyTorch version (GPU?): 1.8.1+cu111 (True)
- Tensorflow version (GPU?): 2.5.0 (True)
- 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?: Yes
- Deepspeed version: 0.5.3

### Who can help
@StellaAthena @sgugger @patil-suraj
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## Information

I am running the scripts on a machine with 128G CPU memory and 4 RTX 2080 (11GB).

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

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

## To reproduce

Steps to reproduce the behavior:

Running example training script with 

```bash
transformers/examples/pytorch/language-modeling$ python run_clm.py --model_name_or_path EleutherAI/gpt-neo-125M  --dataset_name wikitext     --dataset_config_name wikitext-2-raw-v1     --do_train     --do_eval     --output_dir /tmp/test-clm --overwrite_output_dir
```

And got OOM error. I guess RTX2080 should be enough to fit a 125M model?

And besides I tried deepspeed with this command on the machine with 4 RTX 2080
```bash
transformers/examples/pytorch/language-modeling$ deepspeed --num_gpus 4 run_clm.py     --model_name_or_path EleutherAI/gpt-neo-125M     --dataset_name wikitext     --dataset_config_name wikitext-2-raw-v1     --do_train     --do_eval     --output_dir /tmp/test-clm --deepspeed ../../../tests/deepspeed/ds_config_zero3.json --overwrite_output_dir
```
Still got OOM error. I tried to vary `-num_gpus` from 1 to 4. 

Use gpt-2, gpt-2-medium, gpt-neo-1.3B, gpt-neo-2.7B give the same OOM error (with or without deepspeed).
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## Expected behavior
The example script should run without producing an error.

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

Please use the [forums](https://discuss.huggingface.co/) for questions like this, as we use the issues for bugs and feature requests only. You should probably reduce the sequence length you are using (with `--block_size`) to avoid the OOM issue, since it defaults to a large number, or reduce the batch size.<|||||>Ok thanks, sorry I was unaware of the forums. 