metadata
base_model: stabilityai/stable-diffusion-xl-base-1.0
library_name: diffusers
license: openrail++
instance_prompt: google illustration
widget:
- text: google illustration, a winter pond, realistic, simplistic
output:
url: images/example_vr32zqhzt.png
- text: >-
google illustration, chameleon on branch, cartoon style, vibrant colors,
green and yellow, tropical setting, simple background, detailed leaves,
playful design
output:
url: images/example_9f0onnif2.png
- text: >-
google illustration, orca leaping out of ocean, detailed, realistic, blue,
white, and black
output:
url: images/example_mkwjkqhvs.png
- text: >-
google illustration, a coffee cup on a windowsill, geometric, natural
light
output:
url: images/example_sfxutonf9.png
- text: >-
google illustration, blue watch, simplistic design, clean lines,
minimalistic
output:
url: images/example_03ldp8bmf.png
- text: >-
google illustration, a barn in spring, green, brown, simplistic, vibrant
colors, minimalistic
output:
url: images/example_8rowj27tp.png
tags:
- text-to-image
- text-to-image
- diffusers-training
- diffusers
- lora
- template:sd-lora
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
SDXL LoRA DreamBooth - qingy2024/GI_LoRA (Google Illustrations Preview)
Model description
These are qingy2024/GI_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 google illustration to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]