GPU is needed for quantization in M2 MacOS
### System Info

M2 MacOS that has 12 CPU and 38 GPU, 96GB processor, 2TB storage

### Who can help?

_No response_

### Information

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

### Tasks

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

### Reproduction

I am getting this issue " No GPU found. A GPU is needed for quantization." for the following code snippet trying to be implemented in M2 MacOS that has 12 CPU and 38 GPU in it. How is QLORA/quantization will work on M2 MacOS systems that has "mps" in it?

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig

model_id = "EleutherAI/gpt-neox-20b"
bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_use_double_quant=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16
)

tokenizer = AutoTokenizer.from_pretrained(model_id)
# model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config) #, device_map={"":0})
model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config, device=torch.device('cpu'))


### Expected behavior

I expect the code will run on "mps" of M2 MacOS
No, the bitsandbytes library only works on CUDA GPU.<|||||>To get around this error I set load_in_8bit=False:
``` AutoModelForSeq2SeqLM.from_pretrained(model_id,load_in_8bit=False)  ```<|||||>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.