`model.safetensors` missing in model file not found error in default case
### System Info

System info isn't super relevant here since the confusion is really just an just an error message string. I just reproduced in a CPU instance but this is applicable whenever model loading is needed.
- `transformers` version: 4.40.1
- Platform: Linux-6.1.58+-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.22.2
- Safetensors version: 0.4.3
- Accelerate version: 0.29.3
- Accelerate config: 	not found
- PyTorch version (GPU?): 2.2.1+cu121 (False)
- Tensorflow version (GPU?): 2.15.0 (False)
- Flax version (CPU?/GPU?/TPU?): 0.8.2 (cpu)
- Jax version: 0.4.26
- JaxLib version: 0.4.26
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No


### Who can help?

Not sure who most recently worked on `modeling_util.py` or model loading parts. Please feel free to point me to the right person

### 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

Setup has safetensors library installed

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

# this is just a cloned example GPTQ quant model. 
# The point of this is that this repo contains a `gptq_model-4bit-128g.safetensors` file (default naming by AutoGPTQ library), but not `model.safetensors`.
# Not having a `.safetensors` and/or any modeling files produces the same behavior
# Note how use_safetensors is not passed in
# With safetensors library, it will default to `use_safetensors=None` inside `.from_pretrained()` function
tokenizer = AutoTokenizer.from_pretrained("davidxmle/Llama-3-8B-Instruct-GPTQ-4-Bit-Debug")
model = AutoModelForCausalLM.from_pretrained("davidxmle/Llama-3-8B-Instruct-GPTQ-4-Bit-Debug")
```

An error will get thrown
```
davidxmle/Llama-3-8B-Instruct-GPTQ-4-Bit-Debug does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack.
```
 Error message has no mention of `.safetensors` file is an accepted model file format.


### Expected behavior

This isn't necessarily a bug but rather a confusing error message. I initially noticed this issue when I uploaded a GPTQ quant model made using the AutoGPTQ library to huggingface but some folks reported that they are getting the error above `does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack.` One would have immediately assumed `safetensors` is not an accepted file format and I must not use `safetensors` but rather use one of the models listed above, since I do have a `safetensors` file in the repo.

Upon further investigation I realized that the `use_safetensors` is an optional argument to be passed in added in https://github.com/huggingface/transformers/pull/22083. This means `use_safetensors` can either be `False` if explicitly defined as `False` or does not have safetensors package installed, `True` if explicitly defined as so, or, **most importantly `use_safetensors` will default to`None` if not specified but has safetensors installed**.

The pull request added in https://github.com/huggingface/transformers/pull/22083, does add an error message specifically for safe tensors, but it uses `elif use_safetensors:` for the error message specific for safetensors, and used `elif use_safetensors is not False` elsewhere... `elif use_safetensors:` evaluates both the default case with `None` value and explict `False` case to false, so the error message containing safetensors in the default case never reached there. I do believe this is the expected behavior since we do not want to only mention safetensors is missing in the default case. 

However, in the case where the `use_safetensors` is defaulted to `None` when the arg is not passed in and model file is missing, there is no mention of `.safetensors` is supported. This should be comprehensive list of all modeling files that are supported, including `model.safetensors`.

I have put together a super simple PR and changed the unit test to address this.