README.md

---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=RentCivit&allowDerivatives=False&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- style
- split
- split style
- splitstyle

base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: splitstyle
widget:
- text: ' '
  
  output:
    url: >-
      23409234.jpeg
- text: ' '
  
  output:
    url: >-
      23410932.jpeg
- text: ' '
  
  output:
    url: >-
      23409233.jpeg

---

# 4art style 

<Gallery />





## Model description

<p>First attempt at creating a LoRa that recruits for different traditional art styles. Trained on close-up portraits. Might take a bit more tinkering as it tends to just have two panels instead of four. anyway while i work out the bugs enjoy </p>

## Trigger words
You should use `splitstyle`, `evang`, `split_style` to trigger the image generation.
    

## Download model

Weights for this model are available in Safetensors format.

[Download](/brushpenbob/4art-style/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('brushpenbob/4art-style', weight_name='4art_style.safetensors')
image = pipeline('`splitstyle`, `evang`, `split_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)