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

base_model: runwayml/stable-diffusion-v1-5
instance_prompt: evang
widget:
- text: ' '
  
  output:
    url: >-
      22835081.jpeg
- text: ' '
  
  output:
    url: >-
      22890901.jpeg
- text: ' '
  
  output:
    url: >-
      22836976.jpeg
- text: ' '
  
  output:
    url: >-
      22838541.jpeg
- text: ' '
  
  output:
    url: >-
      22844362.jpeg
- text: ' '
  
  output:
    url: >-
      22888589.jpeg

---

# MidJourney anime style 

<Gallery />





## Model description

<p>data set trained off of midjourney anime style images, mostly people</p><p></p><div data-youtube-video><iframe width="640" height="480" allowfullscreen="true" autoplay="false" disablekbcontrols="false" enableiframeapi="false" endtime="0" ivloadpolicy="0" loop="false" modestbranding="false" origin playlist src="https://www.youtube.com/embed/QynE0UGQhRs" start="0"></iframe></div>

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

## Download model

Weights for this model are available in Safetensors format.

[Download](/brushpenbob/midjourney-anime-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('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('brushpenbob/midjourney-anime-style', weight_name='MJstyle_epoch_6.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)