Instructions to use ksj1304/testformerge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ksj1304/testformerge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ksj1304/testformerge", 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:
- 43fe4392ccb1676ce3a4fb62e5df92c6fbc8fcdbaa1729b1f136a15d16e37a9e
- Size of remote file:
- 492 MB
- SHA256:
- 35b152d0f55615e80c1b4f1caed8b030a3520ba8e3d97fa9961fa275e75e3f28
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