Instructions to use nitrosocke/Ghibli-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Ghibli-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/Ghibli-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
Commit History
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Adding `safetensors` variant of this model (#15)
- Adding `safetensors` variant of this model (75f68c4d7a51cf573ded51526297fd2b8cdb84ff) Co-authored-by: Steven Liu <stevhliu@users.noreply.huggingface.co>7600fd7
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Add `scale_factor` to vae config. (#10)
- Add `scale_factor` to vae config. (2031c4bcd7036ca6b091e894e1e105320135e850) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>441c2fd
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Add Diffusers weights (#2)
- Add Diffusers weights (672590a74439a20a07f93695e3a3f807cf928434) Co-authored-by: Ahsen Khaliq <akhaliq@users.noreply.huggingface.co>5b57f12