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
- disney
- retro
- style
- cartoon
- the protoart

base_model: black-forest-labs/FLUX.1-dev
instance_prompt: egdisney
widget:
- text: ' '
  
  output:
    url: >-
      26130647.jpeg
- text: ' '
  
  output:
    url: >-
      26131291.jpeg
- text: ' '
  
  output:
    url: >-
      26129678.jpeg
- text: ' '
  
  output:
    url: >-
      26129677.jpeg
- text: ' '
  
  output:
    url: >-
      26129676.jpeg

---

# Flux retro Disney v2 

<Gallery />





## Model description

<p>Second version of my Disney model with a higher epoch training</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 `egdisney` to trigger the image generation.
    

## Download model

Weights for this model are available in Safetensors format.

[Download](/brushpenbob/flux-retro-disney-v2/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('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('brushpenbob/flux-retro-disney-v2', weight_name='Flux_retro_Disney_v2.safetensors')
image = pipeline('`egdisney`').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)