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---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=RentCivit&allowDerivatives=False&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- graffiti
- style
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: graffiti_sticker
widget:
- text: ' '
output:
url: >-
9305169.jpeg
- text: ' '
output:
url: >-
9305029.jpeg
- text: ' '
output:
url: >-
9315678.jpeg
---
# graffiti_2024
<Gallery />
## Model description
<p>Use words like "graffiti" "graffiti art", or urban art to trigger the model</p><p></p><p></p>
## Trigger words
You should use `graffiti_sticker`, `graffiti` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/brushpenbob/graffiti-2024/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('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('brushpenbob/graffiti-2024', weight_name='graffiti_2024.safetensors')
image = pipeline('`graffiti_sticker`, `graffiti`').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)
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