Modelpublic

ntc-ai/SDXL-LoRA-slider.sacred-geometry

sourceHugging Facemitupdated 3y agoView on Hugging Face

1likes14downloads

Model Card

language:

—en thumbnail: "images/evaluate/sacred geometry.../sacred geometry173.0.png" widget:
—text: sacred geometry output: url: images/sacred geometry173.0.png
—text: sacred geometry output: url: images/sacred geometry193.0.png
—text: sacred geometry output: url: images/sacred geometry203.0.png
—text: sacred geometry output: url: images/sacred geometry213.0.png
—text: sacred geometry output: url: images/sacred geometry223.0.png tags:
—text-to-image
—stable-diffusion-xl
—lora
—template:sd-lora
—template:sdxl-lora
—sdxl-sliders
—ntcai.xyz-sliders
—concept
—diffusers license: "mit" inference: false instanceprompt: "sacred geometry" basemodel: "stabilityai/stable-diffusion-xl-base-1.0" ---

ntcai.xyz slider - sacred geometry (SDXL LoRA)

Strength: -3	Strength: 0	Strength: 3
<img src="images/sacred geometry17-3.0.png" width=256 height=256 />	<img src="images/sacred geometry170.0.png" width=256 height=256 />	<img src="images/sacred geometry173.0.png" width=256 height=256 />
<img src="images/sacred geometry19-3.0.png" width=256 height=256 />	<img src="images/sacred geometry190.0.png" width=256 height=256 />	<img src="images/sacred geometry193.0.png" width=256 height=256 />
<img src="images/sacred geometry20-3.0.png" width=256 height=256 />	<img src="images/sacred geometry200.0.png" width=256 height=256 />	<img src="images/sacred geometry203.0.png" width=256 height=256 />

Download

Weights for this model are available in Safetensors format.

Trigger words

You can apply this LoRA with trigger words for additional effect:

sacred geometry

Use in diffusers

python

from diffusers import StableDiffusionXLPipeline
from diffusers import EulerAncestralDiscreteScheduler
import torch

pipe = StableDiffusionXLPipeline.from_single_file("https://huggingface.co/martyn/sdxl-turbo-mario-merge-top-rated/blob/main/topRatedTurboxlLCM_v10.safetensors")
pipe.to("cuda")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)

# Load the LoRA
pipe.load_lora_weights('ntc-ai/SDXL-LoRA-slider.sacred-geometry', weight_name='sacred geometry.safetensors', adapter_name="sacred geometry")

# Activate the LoRA
pipe.set_adapters(["sacred geometry"], adapter_weights=[2.0])

prompt = "medieval rich kingpin sitting in a tavern, sacred geometry"
negative_prompt = "nsfw"
width = 512
height = 512
num_inference_steps = 10
guidance_scale = 2
image = pipe(prompt, negative_prompt=negative_prompt, width=width, height=height, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
image.save('result.png')

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Other resources

—CivitAI - Follow ntc on Civit for even more LoRAs
—ntcai.xyz - See ntcai.xyz to find more articles and LoRAs