metadata
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
- glitch
- style
- artstyle
- corrupted
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: gltch artstyle
widget:
- text: ' '
output:
url: 2462614.jpeg
- text: Tokyo city skyline sunset vaporwave (gltch artstyle)
output:
url: 2460637.jpeg
- text: dinosaur eating broccoli (gltch artstyle)
output:
url: 2460765.jpeg
- text: ' '
output:
url: 2460488.jpeg
- text: ' '
output:
url: 2460489.jpeg
- text: dinosaur eating broccoli (gltch artstyle)
output:
url: 2460766.jpeg
- text: ' '
output:
url: 2460662.jpeg
- text: ' '
output:
url: 2462615.jpeg
- text: ' '
output:
url: 2460254.jpeg
- text: ' '
output:
url: 2460256.jpeg
GLTCH artstyle "corrupt CR2 Canon RAW files" 218MB LoRA
Model description
Trained on corrupted CR2 RAW files taken from a Canon 6D with Magic Lantern installed.
I thought the strange colorful banding from these photographs made for an useful LoRA.
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Trigger words
You should use gltch artstyle
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('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('DoctorDiffusion/gltch-artstyle-corrupt-cr2-canon-raw-files-218mb-lora', weight_name='DD-gltch-artstyle-XL-v1.safetensors')
image = pipeline('`gltch artstyle`').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers