diffusers text-to-image stable-diffusion lora template:sd-lora migrated style characters creature protoart base_model:stabilityai/stable-diffusion-xl-base-1.0 base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0 license:other region:us
---
base_model: stabilityai/stable-diffusion-xl-base-1.0
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
- characters
- creature
- protoart
instance_prompt: Evang
widget:
- text: ' '
  output:
    url: 22694387.jpeg
- text: ' '
  output:
    url: 22694388.jpeg
- text: ' '
  output:
    url: 20059855.jpeg
- text: ' '
  output:
    url: 20059857.jpeg
- text: ' '
  output:
    url: 20059856.jpeg
---

# LBV4XL 

<Gallery />





## Model description

<p>Updated data set originally used for this model here </p><p><a target="_blank" rel="ugc" href="https://civitai.com/models/113840/lost-bear-chibi-sketch?modelVersionId=123019">https://civitai.com/models/113840/lost-bear-chibi-sketch?modelVersionId=123019</a></p>

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

## Download model

Weights for this model are available in Safetensors format.

[Download](/brushpenbob/lbv4xl/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/lbv4xl', weight_name='LBV4XL.safetensors')
image = pipeline('`Evang`').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)

