---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Rent&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- style
- laundry
- cloth
- laundry art
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: LaundryArt
widget:
- text: 'Wonderwoman LaundryArt '
output:
url: >-
5594409.jpeg
- text: 'Rick Sanchez LaundryArt '
output:
url: >-
5594414.jpeg
- text: 'A crazy clown LaundryArt '
output:
url: >-
5594407.jpeg
- text: 'Pikachu LaundryArt '
output:
url: >-
5594410.jpeg
- text: 'A cute dog LaundryArt '
output:
url: >-
5594408.jpeg
- text: 'Shrek and Olaf on a frozen field LaundryArt '
output:
url: >-
5594413.jpeg
- text: 'Snoop Dogg LaundryArt '
output:
url: >-
5594405.jpeg
- text: 'A socially awkward potato LaundryArt '
output:
url: >-
5594412.jpeg
- text: 'American gothic LaundryArt '
output:
url: >-
5594406.jpeg
---
# LaundryArt LoRA
LaundryArt is, well, a sort of art people make by arranging their Laundry in a certain way and adding some objects into the mix
## Trigger words You should use `LaundryArt` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/Norod78/laundryart-lora/tree/main) them in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Norod78/laundryart-lora', weight_name='LaundryArt_LoRA_r16-000006.safetensors') image = pipeline('American gothic LaundryArt ').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)