Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Instructions to use Antiraedus/Violet-Evergarden-Style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Antiraedus/Violet-Evergarden-Style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Antiraedus/Violet-Evergarden-Style", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of a beautiful anime city in vioeva style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth model for the vioeva concept trained by Antiraedus on the Antiraedus/Violet-Evergarden dataset.
I FORGOT IT WAS GRAYSCALED
This is a Stable Diffusion model fine-tuned on the vioeva concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of a girl in vioeva style
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
Description
Violet Evergarden!!!! Dataset is located here
This is a Stable Diffusion model fine-tuned on style images for the wildcard theme.
Examples
"a photo of a beautiful anime city in vioeva style"

Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Antiraedus/Violet-Evergarden-Style')
image = pipeline().images[0]
image
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