fix style

Signed-off-by: YAO Matrix <[email protected]>

Author: yao-matrix

src/diffusers/pipelines/pipeline_utils.py

@@ -1205,7 +1205,7 @@ def enable_sequential_cpu_offload(self, gpu_id: Optional[int] = None, device: Un
         r"""
         Offloads all models to CPU using 🤗 Accelerate, significantly reducing memory usage. When called, the state
         dicts of all `torch.nn.Module` components (except those in `self._exclude_from_cpu_offload`) are saved to CPU
-        and then moved to `torch.device('meta')` and loaded to GPU only when their specific submodule has its `forward`
+        and then moved to `torch.device('meta')` and loaded to accelerator only when their specific submodule has its `forward`
         method called. Offloading happens on a submodule basis. Memory savings are higher than with
         `enable_model_cpu_offload`, but performance is lower.
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -380,6 +380,7 @@ def encode_prompt(
                 adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
             else:
                 scale_lora_layers(self.text_encoder, lora_scale)
+
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
         elif prompt is not None and isinstance(prompt, list):