Instructions to use Kurudaz/hyper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kurudaz/hyper with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kurudaz/hyper", 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:
- 93c56ddbc08da60186f8a83cf27671ff644e152fa9d2d348d262de32d5c5b1fe
- Size of remote file:
- 5.14 GB
- SHA256:
- 772b12ec4c32843fc7d521d2c5722b057ee2be3d102d796fe3707415fbc25f66
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