Instructions to use nitrosocke/Arcane-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Arcane-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/Arcane-Diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Req: Runeterra art for future training
#27
by torridgristle - opened
The League of Legends spin-off Legends of Runeterra has a lot of great art for the cards (all widescreen except for spells unfortunately) and have the same general style, but with some more variety in content. Like boats and dragons and bears, fantasy and steampunk and pirates, etc.
I think this would add a lot to the model if included in the dataset for future training, if any is planned.