Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
image-to-image
nitrosocke
Instructions to use Yntec/GhibliDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/GhibliDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/GhibliDiffusion", 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
- Xet hash:
- bede401f52b803c609d2a993b50781e2afa763834cdd52d81c102708ab19d7f2
- Size of remote file:
- 492 MB
- SHA256:
- 001a8f7f7141e30cf88109d74c269f449b435585735534990201bd66a8aa0d78
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