---
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)