[LoRA](https://hf.co/docs/peft/conceptual_guides/adapter#low-rank-adaptation-lora) is a lightweight adapter that is fast and easy to train, making them especially popular for generating images in a certain way or style. These adapters are commonly stored in a safetensors file, and are widely popular on model sharing platforms like [civitai](https://civitai.com/).  
LoRAs are loaded into a base model with the [`~loaders.StableDiffusionLoraLoaderMixin.load_lora_weights`] method.  
```py
from diffusers import StableDiffusionXLPipeline
import torch

# base model
pipeline = StableDiffusionXLPipeline.from_pretrained(
"Lykon/dreamshaper-xl-1-0", torch_dtype=torch.float16, variant="fp16"
).to("cuda")

# download LoRA weights
!wget https://civitai.com/api/download/models/168776 -O blueprintify.safetensors

# load LoRA weights
pipeline.load_lora_weights(".", weight_name="blueprintify.safetensors")
prompt = "bl3uprint, a highly detailed blueprint of the empire state building, explaining how to build all parts, many txt, blueprint grid backdrop"
negative_prompt = "lowres, cropped, worst quality, low quality, normal quality, artifacts, signature, watermark, username, blurry, more than one bridge, bad architecture"

image = pipeline(
prompt=prompt,
negative_prompt=negative_prompt,
generator=torch.manual_seed(0),
).images[0]
image
```  
<div class="flex justify-center">
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/blueprint-lora.png"/>
</div>
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