Instructions to use nagolinc/sd-dune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nagolinc/sd-dune with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nagolinc/sd-dune", 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
This model was trained based off of https://huggingface.co/runwayml/stable-diffusion-v1-5 for 15000 steps using 2.5k images from https://dune.fandom.com/wiki/Dune_Wiki
Usage:
from diffusers import StableDiffusionPipeline
import torch
pipe=StableDiffusionPipeline.from_pretrained("nagolinc/sd-dune",dtype=torch.float16)
pipe.to("cuda")
image=pipe("shai hulud").images[0]
"dune"
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