@@ -203,10 +203,10 @@ class KandinskyCombinedPipeline(DiffusionPipeline):
defenable_sequential_cpu_offload(self,gpu_id=0):
r"""
Offloads all models (`unet`, `text_encoder`, `vae`, and `safety checker` state dicts) to CPU using 🤗 Accelerate, significantly reducing memory usage. Models are moved to a
`torch.device('meta')` and loaded on a GPU only when their specific submodule's `forward` method is called.
Offloading happens on a submodule basis. Memory savings are higher than using
`enable_model_cpu_offload`, but performance is lower.
Offloads all models (`unet`, `text_encoder`, `vae`, and `safety checker` state dicts) to CPU using 🤗
Accelerate, significantly reducing memory usage. Models are moved to a `torch.device('meta')` and loaded on a
GPU only when their specific submodule's `forward` method is called. Offloading happens on a submodule basis.
Memory savings are higher than using `enable_model_cpu_offload`, but performance is lower.