metadata
license: other
license_name: bespoke-lora-trained-license
license_link: >-
https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- wow
- style
- world of warcraft
- styled
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: WoW Screenshot
widget:
- text: >-
a doge dog in a leather jacket riding a motorcycle in a desert, WoW
Screenshot
output:
url: 28858186.jpeg
- text: >-
a horse is a DJ at a night club, fish eye lens, smoke machine, lazer
lights, holding a martini WoW Screenshot
output:
url: 28858188.jpeg
- text: >-
woman with red hair, playing chess at the park, bomb going off in the
background WoW Screenshot
output:
url: 28858187.jpeg
- text: Wonderwoman flying with golden wings, WoW Screenshot
output:
url: 28858185.jpeg
- text: A socially awkward potato WoW Screenshot
output:
url: 28858189.jpeg
- text: eiffel tower WoW Screenshot
output:
url: 28858191.jpeg
- text: The girl with a pearl earring WoW Screenshot
output:
url: 28858190.jpeg
WoW Screenshot [FLUX]
(CivitAI)
Model description
Make your images look like they are a screenshot from World of Warcraft
Use a LoRA weight scale between 1.5 to 2.0
Use "WoW Screenshot" in your prompts to trigger the style
Trigger words
You should use WoW Screenshot
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
device = "cuda" if torch.cuda.is_available() else "cpu"
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Norod78/wow-screenshot-flux', weight_name='Flux-WoW-Screenshot-LoRA.safetensors')
image = pipeline('The girl with a pearl earring WoW Screenshot').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers