Instructions to use Ryzan/fantasy-diffusion-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ryzan/fantasy-diffusion-v0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Ryzan/fantasy-diffusion-v0", 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
metadata
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
fantasy-diffusion-v0 diffusion model trained by Ryzan with DreamBooth
fantasy-diffusion-v1 is already out
v1 has better rendering than v0
see v1 at: https://huggingface.co/Ryzan/fantasy-diffusion-v1
v0 is currently a test model
This model is trained on 400 images of semi-realistic fantasy art
This model does not use any finetuning techniques such as face restoration or in-painting as of yet
Sample pictures of this concept:

.jpg)

.jpg)

.jpg)