README.md

---
license: other
license_name: bespoke-lora-trained-license
license_link: >-
  https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Rent&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- disney
- pixar
- dreamworks
- style
- cartoon
- sdxl style lora
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: DreamDisPix style
widget:
- text: 'Shrek playing with olaf in a frozen field DreamDisPix style '
  output:
    url: 4857923.jpeg
- text: 'The girl from the incredibles shooting a laser gun  DreamDisPix style '
  output:
    url: 4857954.jpeg
- text: 'The girl with a pearl earring  DreamDisPix style  '
  output:
    url: 4857994.jpeg
- text: 'Snoop Dogg  DreamDisPix style  '
  output:
    url: 4857995.jpeg
- text: 'A mighty dragon at the dentist DreamDisPix style '
  output:
    url: 4858005.jpeg
- text: 'A cute dragon playing with Eevee DreamDisPix style '
  output:
    url: 4857996.jpeg
- text: 'Zombie Cinderella has rissen from the dead  DreamDisPix style '
  output:
    url: 4858004.jpeg
- text: 'Santa riding a might dragon DreamDisPix style '
  output:
    url: 4858026.jpeg
- text: 'Pocahontas riding a Zebra  DreamDisPix style '
  output:
    url: 4858031.jpeg
- text: 'American gothic  DreamDisPix style  '
  output:
    url: 4858028.jpeg
datasets:
- Norod78/DreamDisPix-blip2-captions
---

# Dream Dis Pix XL 

<Gallery />



([CivitAI](https://civitai.com/models/242711))

## Model description

<p><span>A (kinda failed) attempt to train an SDXL LoRA model upon on a mixed style dataset of images from </span><strong><span>Dream</span></strong><span>works, </span><strong><span>Dis</span></strong><span>ney and </span><strong><span>Pix</span></strong><span>ar. I have uploaded this</span><a rel="ugc" href="https://huggingface.co./datasets/Norod78/DreamDisPix-blip2-captions"><span> Blip2-Captioned Dataset to Huggingface</span></a><span>. </span><br /><br /><span>I usually prefer to train in LoRA ranks 4-16 because so far it always seemed to be enough and provided a reasonably small checkpoint but in this case, I only started getting results when I went for Rank-32, even tried 24 and it was not enough.</span><br /><br />M<span>y conclusion is that it should have probably been trained as several different lower ranked LoRAs each for the specific visual sub-style and it would have probably looked way better for each.</span></p>

## Trigger words
You should use `DreamDisPix style` to trigger the image generation.
    

## Download model

Weights for this model are available in Safetensors format.

[Download](/Norod78/dream-dis-pix-xl/tree/main) them in the Files & versions tab.

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('Norod78/dream-dis-pix-xl', weight_name='SDXL-DreamDisPix-Lora-r32.safetensors')
image = pipeline('American gothic  DreamDisPix style  ').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co./docs/diffusers/main/en/using-diffusers/loading_adapters)