---
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

---

<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->


# SDXL LoRA DreamBooth - qingy2024/GI_LoRA (Google Illustrations Preview)

<Gallery />

## Model description

These are qingy2024/GI_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.

The weights were trained  using [DreamBooth](https://dreambooth.github.io/).

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](qingy2024/GI_LoRA/tree/main) them in the Files & versions tab.



## Intended uses & limitations

#### How to use

```python
# 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]