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ntc-ai/SDXL-LoRA-slider.shiny

sourceHugging Facemitupdated 3y agoView on Hugging Face
1likes51downloads
Model Card

language:

  • en thumbnail: "images/evaluate/shiny...dull/shiny173.0.png" widget:
  • text: shiny output: url: images/shiny173.0.png
  • text: shiny output: url: images/shiny193.0.png
  • text: shiny output: url: images/shiny203.0.png
  • text: shiny output: url: images/shiny213.0.png
  • text: shiny output: url: images/shiny223.0.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: "shiny" basemodel: "stabilityai/stable-diffusion-xl-base-1.0" ---

ntcai.xyz slider - shiny (SDXL LoRA)

Strength: -3Strength: 0Strength: 3
<img src="images/shiny17-3.0.png" width=256 height=256 /><img src="images/shiny170.0.png" width=256 height=256 /><img src="images/shiny173.0.png" width=256 height=256 />
<img src="images/shiny19-3.0.png" width=256 height=256 /><img src="images/shiny190.0.png" width=256 height=256 /><img src="images/shiny193.0.png" width=256 height=256 />
<img src="images/shiny20-3.0.png" width=256 height=256 /><img src="images/shiny200.0.png" width=256 height=256 /><img src="images/shiny203.0.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:

shiny

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.shiny', weight_name='shiny.safetensors', adapter_name="shiny")

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

prompt = "medieval rich kingpin sitting in a tavern, shiny"
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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Your support on Patreon will allow us to continue developing and refining new models.

Other resources

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