docs

Author: sayakpaul

docs/source/en/tutorials/using_peft_for_inference.md

@@ -315,6 +315,8 @@ pipeline.load_lora_weights(
 > [!TIP]
 > Move your code inside the `with torch._dynamo.config.patch(error_on_recompile=True)` context manager to detect if a model was recompiled. If a model is recompiled despite following all the steps above, please open an [issue](https://github.com/huggingface/diffusers/issues) with a reproducible example.
 
+If you expect to varied resolutions during inference with this feature, then make sure set `dynamic=True` during compilation. Refer to [this document](../optimization/fp16#dynamic-shape-compilation) for more details.
+
 There are still scenarios where recompulation is unavoidable, such as when the hotswapped LoRA targets more layers than the initial adapter. Try to load the LoRA that targets the most layers *first*. For more details about this limitation, refer to the PEFT [hotswapping](https://huggingface.co/docs/peft/main/en/package_reference/hotswap#peft.utils.hotswap.hotswap_adapter) docs.
 
 ## Merge