Repository: transformers
Issue: safetensors_rust.SafetensorError: Error while serializing: IoError(Os { code: 5, kind: Uncategorized, message: "Input/output error" })
Labels: bug

### System Info

- `transformers` version: 4.47.1
- Platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.27.0
- Safetensors version: 0.4.5
- Accelerate version: 1.2.1
- Accelerate config:    not found
- PyTorch version (GPU?): 2.5.1+cu124 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: No
- Using GPU in script?: Yes
- GPU type: NVIDIA GeForce RTX 3060 Laptop GPU

### Who can help?

@SunMarc @MekkCyber 

### 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

Error:
```
Traceback (most recent call last):
  File "/mnt/d/Python_Projects/Jupyter/other/call-center-prompter/debug/quant/check-quantizations.py", line 31, in <module>
    quantize_gptq(model_id=model_id, quant_config=gptq_config, prefix_dir=prefix_dir)
  File "/mnt/d/Python_Projects/Jupyter/other/call-center-prompter/debug/quant/gptq_quantize.py", line 32, in quantize_gptq
    model.save_pretrained(prefix_dir + quant_path)
  File "/mnt/d/Python_Projects/Jupyter/other/call-center-prompter/debug/quant/venv-wsl2/lib/python3.12/site-packages/transformers/modeling_utils.py", line 3034, in save_pretrained
    safe_save_file(shard, os.path.join(save_directory, shard_file), metadata={"format": "pt"})
  File "/mnt/d/Python_Projects/Jupyter/other/call-center-prompter/debug/quant/venv-wsl2/lib/python3.12/site-packages/safetensors/torch.py", line 286, in save_file
    serialize_file(_flatten(tensors), filename, metadata=metadata)
safetensors_rust.SafetensorError: Error while serializing: IoError(Os { code: 5, kind: Uncategorized, message: "Input/output error" })
```
Code:
```
import os
import logging
from transformers import AutoModelForCausalLM, AutoTokenizer, GPTQConfig
from huggingface_hub import login, snapshot_download

logger = logging.getLogger(__name__)

logger.info("Logging in HF")
login(token=<mytoken>)

def quantize_gptq(model_id: str, quant_config: dict, prefix_dir: str = './') -> str:
    prefix_dir += '/' if prefix_dir[-1] != '/' else ''
    model_path = prefix_dir + model_id.split('/')[1] if os.path.exists(prefix_dir + model_id.split('/')[1]) else model_id
    quant_path = model_id.split('/')[1] + f"-GPTQ-{quant_config['bits']}bit"

    if os.path.exists(prefix_dir + quant_path):
        logger.info("Skipping GPTQ quantization because it already exists")
    else:
        tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=True)
        config = GPTQConfig(**quant_config, dataset="c4", tokenizer=tokenizer) # exllama_config={"version":2}

        model = AutoModelForCausalLM.from_pretrained(
            model_path,
            device_map="auto",
            trust_remote_code=False,
            quantization_config=config,
            revision="main"
        )

        logger.info("Save GPTQ quantized model")
        os.makedirs(prefix_dir + quant_path, exist_ok=True)
        model.save_pretrained(prefix_dir + quant_path)
        tokenizer.save_pretrained(prefix_dir + quant_path)

        logger.info("Push to hub GPTQ quantized model")
        model.push_to_hub(quant_path)
        tokenizer.push_to_hub(quant_path)

    return prefix_dir + quant_path
```

### Expected behavior

Model saving without errors