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base_model: stabilityai/stable-diffusion-xl-base-1.0
library_name: diffusers
license: openrail++
instance_prompt: an icon of trpfrog
widget:
  - text: an icon of trpfrog eating ramen
    output:
      url: image_0.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_1.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_2.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_3.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_4.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_5.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_6.png
  - text: an icon of trpfrog eating ramen
    output:
      url: image_7.png
tags:
  - text-to-image
  - diffusers-training
  - diffusers
  - lora
  - template:sd-lora
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
  - text-to-image
  - text-to-image
  - diffusers-training
  - diffusers
  - lora
  - template:sd-lora
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
datasets:
  - trpfrog/trpfrog-icons
  - Prgckwb/trpfrog-icons-dreambooth

SDXL LoRA DreamBooth - Prgckwb/trpfrog-sdxl-lora

Model description

These are Prgckwb/trpfrog-sdxl-lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.

The weights were trained using DreamBooth.

LoRA for the text encoder was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.

Trigger words

You should use an icon of "trpfrog" to trigger the image generation.

How to use

from diffusers import DiffusionPipeline
import torch

base_model_id = 'stabilityai/stable-diffusion-xl-base-1.0'
lora_model_id = 'Prgckwb/trpfrog-sdxl-lora'

pipe = DiffusionPipeline.from_pretrained(
  base_model_id, torch_dtype=torch.float16
).to("cuda")
pipe.load_lora_weights(lora_model_id)

image = pipe(
  "an icon of trpfrog",
  num_inference_steps=25
).images[0]
image.save('trpfrog.png')