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
File size: 1,368 Bytes
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license: creativeml-openrail-m
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**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](https://huggingface.co/nitrosocke)
**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_ |