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ntc-ai/SDXL-LoRA-slider.Product-Photo

sourceHugging Facemitupdated 3y agoView on Hugging Face
2likes111downloads
Model Card

language:

  • —en thumbnail: "images/evaluate/Product Photo.../Product Photo173.0.png" widget:
  • —text: Product Photo output: url: images/Product Photo173.0.png
  • —text: Product Photo output: url: images/Product Photo193.0.png
  • —text: Product Photo output: url: images/Product Photo203.0.png
  • —text: Product Photo output: url: images/Product Photo213.0.png
  • —text: Product Photo output: url: images/Product Photo223.0.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: "Product Photo" basemodel: "stabilityai/stable-diffusion-xl-base-1.0" ---

ntcai.xyz slider - Product Photo (SDXL LoRA)

Strength: -3Strength: 0Strength: 3
<img src="images/Product Photo17-3.0.png" width=256 height=256 /><img src="images/Product Photo170.0.png" width=256 height=256 /><img src="images/Product Photo173.0.png" width=256 height=256 />
<img src="images/Product Photo19-3.0.png" width=256 height=256 /><img src="images/Product Photo190.0.png" width=256 height=256 /><img src="images/Product Photo193.0.png" width=256 height=256 />
<img src="images/Product Photo20-3.0.png" width=256 height=256 /><img src="images/Product Photo200.0.png" width=256 height=256 /><img src="images/Product Photo203.0.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:

Product Photo

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.Product-Photo', weight_name='Product Photo.safetensors', adapter_name="Product Photo")

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

prompt = "medieval rich kingpin sitting in a tavern, Product Photo"
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