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
  - concept
  - split
  - split screen
  - protoart
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: 2splitstyle
widget:
  - text: ' '
    output:
      url: 24440943.jpeg
  - text: ' '
    output:
      url: 24429856.jpeg
  - text: ' '
    output:
      url: 24429858.jpeg
  - text: ' '
    output:
      url: 24429857.jpeg

Splitstyle 2.0

Model description

Second attempt at creating a LoRa that recruits for different traditional art styles.

I realized after the training was already completed. I trained us as a style and not a concept so this is the second attempt added a few more images to the data set up and that helps.

It should now allow you the option to create either two panels or four panel images. with the triggers "2splitstyle" or "4splitstyle"

Trained on close-up portraits. Might take a bit more tinkering as it tends to just have two panels instead of four. anyway while i work out the bugs enjoy

Trigger words

You should use 2splitstyle, 4splitstyle, splitstyle, split_style, evang 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('brushpenbob/splitstyle-2-0', weight_name='Splitstyle_2.0.safetensors')
image = pipeline('`2splitstyle`, `4splitstyle`, `splitstyle`, `split_style`, `evang`').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

Splitstyle 2.0

Model description

I would recommend having the CFG scale set pretty precise, and the step counts relatively high

Trigger words

Download model

Use it with the 🧨 diffusers library