Text-to-Image
Diffusers
ONNX
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use TheyCallMeHex/Ghibli-Diffusion-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheyCallMeHex/Ghibli-Diffusion-ONNX with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheyCallMeHex/Ghibli-Diffusion-ONNX", 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
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("TheyCallMeHex/Ghibli-Diffusion-ONNX", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
OnnxStack
This model has been converted to ONNX and tested with OnnxStack
Ghibli Diffusion
This model was converted to ONNX from Ghibli Diffusion
Sample Images
A ghibli style peaceful countryside scene
| LMS Scheduler | Euler Scheduler | Euler Ancestral Scheduler | DDPM Scheduler | DDIM Scheduler | KDPM2 Scheduler |
|---|---|---|---|---|---|
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Seed: 207582124 GuidanceScale: 7.5 NumInferenceSteps: 30
Ghibli Diffusion Tokens
The tokens for Ghibli Diffusion are:
- ghibli style
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