Instructions to use Bulldeawh/merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bulldeawh/merged with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Bulldeawh/merged", 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:
- 3c1d32abf047780fd0bfbca17d34f6d972c4c9dd75dff299ce54c7d0fcf703b6
- Size of remote file:
- 335 MB
- SHA256:
- 5c3cfa7cedae78adbadc5fed2e301376213f5264bc46f5fd01764d4cf4240f9c
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