Instructions to use nitrosocke/elden-ring-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/elden-ring-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/elden-ring-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 Settings
- Draw Things
- DiffusionBee
license: creativeml-openrail-m
Elden Ring Diffusion
This is the fine-tuned Stable Diffusion model trained on the game art from Elden Ring. Use the tokens elden ring style in your prompts for the effect.
If you enjoy this model, please check out my other models on Huggingface
Portraits rendered with the model:
Landscape Shots rendered with the model:
Sample images used for training:

This model was trained using the diffusers based dreambooth training and prior-preservation loss in 3.000 steps.
Prompt and settings for portraits:
elden ring style portrait of a beautiful woman highly detailed 8k elden ring style Steps: 35, Sampler: DDIM, CFG scale: 7, Seed: 3289503259, Size: 512x704
Prompt and settings for landscapes:
elden ring style dark blue night (castle) on a cliff dark night (giant birds) elden ring style Negative prompt: bright day Steps: 30, Sampler: DDIM, CFG scale: 7, Seed: 350813576, Size: 1024x576