Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
food
Instructions to use shadow/duckduck-roast_duck-heywhale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shadow/duckduck-roast_duck-heywhale with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("shadow/duckduck-roast_duck-heywhale", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of a duckduck roast_duck walking in the water" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- f940cbc11c9b2c800299679b66f3ce0213ba30b0ab3ee308e4c81ab24394e76e
- Size of remote file:
- 8.04 MB
- SHA256:
- 2f9e786c180f847531b2154fc56c094d27dafd825e3a1271e7ede6260306689b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.