image  For both load_lora_weights() and load_attn_procs(), you can pass the cross_attention_kwargs={"scale": 0.5} parameter to adjust how much of the LoRA weights to use. A value of 0 is the same as only using the base model weights, and a value of 1 is equivalent to using the fully finetuned LoRA. To unload the LoRA weights, use the unload_lora_weights() method to discard the LoRA weights and restore the model to its original weights:   Copied pipeline.unload_lora_weights()  Kohya and TheLastBen Other popular LoRA trainers from the community include those by Kohya and TheLastBen. These trainers create different LoRA checkpoints than those trained by 🤗 Diffusers, but they can still be loaded in the same way. Kohya TheLastBen  To load a Kohya LoRA, let’s download the Blueprintify SD XL 1.0 checkpoint from Civitai as an example:   Copied !wget https://civitai.com/api/download/models/168776 -O blueprintify-sd-xl-10.safetensors Load the LoRA checkpoint with the load_lora_weights() method, and specify the filename in the weight_name parameter:   Copied from diffusers import AutoPipelineForText2Image