Cuda Out of memory with DKMPalettizer

## ❓Question

I'm trying to run training-time palletization with n_bits=4.
I always get an out-of-memory error on the first step (despite reducing batch size down to one.)

A few details:
- I'm quantising the stable diffusion v1.5 model.
- I have 24GB of GPU RAM.

Are there any tips to avoid this?
```
config = DKMPalettizerConfig(global_config=ModuleDKMPalettizerConfig(n_bits=4))
palettizer = DKMPalettizer(unet, config)
unet = palettizer.prepare(inplace=True)
unet, optimizer, lr_scheduler = accelerator.prepare(unet, optimizer, lr_scheduler)
```

Start by reproducing the training-time palletization flow with DKMPalettizer.prepare and accelerator.prepare using n_bits=4 on the stable diffusion v1.5 UNet. Measure the first-step GPU allocation and determine whether a documented workaround or a code change is needed; done means training proceeds without the out-of-memory failure.

Written by the indexing model from the issue text.