Why isn’t VRAM being released after training LoRA?

### Describe the bug

When I use train_dreambooth_lora_sdxl.py, the VRAM is not released after training. How can I fix this?

### Reproduction

Not used.

### Logs

_No response_

### System Info

- 🤗 Diffusers version: 0.31.0.dev0
- Platform: Linux-5.14.0-284.25.1.el9_2.x86_64-x86_64-with-glibc2.17
- Running on Google Colab?: No
- Python version: 3.8.20
- PyTorch version (GPU?): 2.2.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Huggingface_hub version: 0.25.2
- Transformers version: 4.45.2
- Accelerate version: 1.0.1
- PEFT version: 0.13.2
- Bitsandbytes version: 0.44.1
- Safetensors version: 0.4.5
- xFormers version: not installed
- Accelerator: NVIDIA H800, 81559 MiB
- Using GPU in script?:
- Using distributed or parallel set-up in script?:

### Who can help?

_No response_

Start by reading train_dreambooth_lora_sdxl.py and reviewing how the training run handles GPU memory with the reported Diffusers, PyTorch, Accelerate, and PEFT versions. Reproduce the run on the stated Linux and NVIDIA H800 setup, then trace what remains allocated after training. Done means the cause is identified and VRAM release is verified after the script finishes.

Written by the indexing model from the issue text.