---
license: other
license_name: bespoke-lora-trained-license
license_link: >-
https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- style
- cartoon
- once upon a time
- flux style
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: ouat cartoon
widget:
- text: 'Girl with a pearl earring ouat cartoon '
output:
url: 58389185.jpeg
- text: American gothic by grant wood ouat cartoon
output:
url: 58389746.jpeg
- text: Dr. who next to their TARDIS ouat cartoon
output:
url: 58389952.jpeg
- text: >-
woman with red hair, playing chess at the park, bomb going off in the
background ouat cartoon
output:
url: 58390257.jpeg
- text: 'A socially awkward potato ouat cartoon '
output:
url: 58390425.jpeg
- text: Wonderwoman eating a small bug
output:
url: images/example_18m7ozy6e.png
datasets:
- Norod78/OnceUponATime-florence2-captions
---
# Once upon a time (cartoon) style [FLUX]
Once Upon a Time... ("Il était une fois...") is a French educational animation franchise.
Use ouat cartoon in your prompts
Fine tuned with Astria AI
A LoRA scale weight of 0.7-1.0 seems to be well
I've made the Florence-2 captioned Dataset availble on Huggingface
## Trigger words You should use `ouat cartoon` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/Norod78/once-upon-a-time-cartoon-style-flux/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 device = "cuda" if torch.cuda.is_available() else "cpu" pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device) pipeline.load_lora_weights('Norod78/once-upon-a-time-cartoon-style-flux', weight_name='ouat_cartoon-OnceUponATimeV3-Flux-2142990.safetensors') image = pipeline('A socially awkward potato ouat cartoon ').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)