selenall/diffusers_retrained

1---2base_model: stabilityai/stable-diffusion-xl-base-1.03library_name: diffusers4license: openrail++5instance_prompt: a painting in sks style6widget:7- text: A painting of sks style8  output:9    url: image_0.png10- text: A painting of sks style11  output:12    url: image_1.png13- text: A painting of sks style14  output:15    url: image_2.png16- text: A painting of sks style17  output:18    url: image_3.png19tags:20- text-to-image21- text-to-image22- diffusers-training23- diffusers24- lora25- template:sd-lora26- stable-diffusion-xl27- stable-diffusion-xl-diffusers28---29 30<!-- This model card has been generated automatically according to the information the training script had access to. You31should probably proofread and complete it, then remove this comment. -->32 33 34# SDXL LoRA DreamBooth - selenall/diffusers_retrained35 36<Gallery />37 38## Model description39 40These are selenall/diffusers_retrained LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.41 42The weights were trained  using [DreamBooth](https://dreambooth.github.io/).43 44LoRA for the text encoder was enabled: True.45 46Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.47 48## Trigger words49 50You should use a painting in sks style to trigger the image generation.51 52## Download model53 54Weights for this model are available in Safetensors format.55 56[Download](selenall/diffusers_retrained/tree/main) them in the Files & versions tab.57 58 59 60## Intended uses & limitations61 62#### How to use63 64```python65# TODO: add an example code snippet for running this diffusion pipeline66```67 68#### Limitations and bias69 70[TODO: provide examples of latent issues and potential remediations]71 72## Training details73 74[TODO: describe the data used to train the model]