metadata
base_model: SG161222/RealVisXL_V5.0
library_name: diffusers
license: openrail++
tags:
- text-to-image
- text-to-image
- diffusers-training
- diffusers
- lora
- template:sd-lora
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
instance_prompt: an OurHood privacy booth
widget:
- text: >-
A photograph, of an Ourhood privacy booth, front view, in a warehouse
eventspace environment, in the style of event photography, silken oak
frame, checkered warm grey exterior fabric, checkered warm grey interior
fabric, curtains, diner seating, pillows
output:
url: image_0.png
- text: >-
A photograph, of an Ourhood privacy booth, front view, in a warehouse
eventspace environment, in the style of event photography, silken oak
frame, checkered warm grey exterior fabric, checkered warm grey interior
fabric, curtains, diner seating, pillows
output:
url: image_1.png
- text: >-
A photograph, of an Ourhood privacy booth, front view, in a warehouse
eventspace environment, in the style of event photography, silken oak
frame, checkered warm grey exterior fabric, checkered warm grey interior
fabric, curtains, diner seating, pillows
output:
url: image_2.png
- text: >-
A photograph, of an Ourhood privacy booth, front view, in a warehouse
eventspace environment, in the style of event photography, silken oak
frame, checkered warm grey exterior fabric, checkered warm grey interior
fabric, curtains, diner seating, pillows
output:
url: image_3.png
SDXL LoRA DreamBooth - Tonioesparza/ourhood_training_dreambooth_lora_2_0_1500
Model description
These are Tonioesparza/ourhood_training_dreambooth_lora_2_0_1500 LoRA adaption weights for SG161222/RealVisXL_V5.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: True.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
Trigger words
You should use an OurHood privacy booth 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]