metadata

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

Model description

Use words like "graffiti" "graffiti art", or urban art to trigger the model

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 them in the Files & versions tab.

Use it with the 🧨 diffusers library

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